Support System Research Articles

The purpose of life is a life of purpose: the work of the Independent Living Fund Scotland

The purpose of the Independent Living Fund Scotland is to empower disabled people to control their own support systems. Established as a ‘closed’ fund in 2015, it has been threatened with eventual closure through attrition. In response, a campaign was organised to open the fund, bolstered by two ‘social return on investment’ evaluations. As a result, the fund was opened in April 2024. This article discusses the background of the Independent Living Fund Scotland, celebrates its opening and attributes its success to being a purpose-led organisation that helps disabled people live purposeful lives.

An innovative technical support system for sustainable construction indicators in Zimbabwe

An innovative technical support system for sustainable construction indicators in Zimbabwe

Emerging technologies and applications in multimodality imaging for ischemic heart disease: current state and future of artificial intelligence

Ischemic heart disease (IHD) is a major global health issue, frequently resulting in myocardial infarction and ischemic cardiomyopathy. Prompt and precise diagnosis is essential to avert complications such as heart failure and sudden cardiac death. Although invasive coronary angiography remains the gold standard for high-risk patients, noninvasive multimodality imaging is becoming more prevalent for those at low-to-intermediate risk. This review evaluated the current state of multimodality imaging in IHD, including echocardiography, nuclear cardiology, cardiac magnetic resonance imaging (MRI), computed tomography (CT) angiography, and invasive coronary angiography. Each modality has distinct strengths and limitations, and their complementary use provides a comprehensive assessment of cardiac health. Integrating artificial intelligence (AI) into imaging workflows holds promise for enhancing diagnostic accuracy and efficiency. AI algorithms can optimize image acquisition, processing, and interpretation of complex imaging data. Emerging technologies like 4D flow MRI, molecular imaging, and hybrid systems [e.g., positron emission tomography (PET)/MRI, PET/CT] integrate anatomical, functional, and molecular data, providing comprehensive insights into cardiac pathology and potentially revolutionizing the management of IHD. This review also explored the clinical applications and impact of multimodality imaging on patient outcomes, emphasizing its role in improving diagnostic precision and guiding therapeutic decisions. Future directions include AI-driven decision support systems and personalized medicine approaches. Addressing regulatory and ethical challenges, such as data privacy and algorithm transparency, is crucial for the broader adoption of these advanced technologies. This review highlighted the transformative potential of AI-enhanced multimodality imaging in improving the diagnosis and management of IHD.

Predicting Student Dropout Rates in Higher Education: A Comparative Study of Machine Learning Algorithms

Recent years have seen a significant increase in study interest in the areas of predicting student performance, avoiding failure, and identifying the variables affecting student dropout. One important indicator in online and open distance learning courses is the student dropout rate. We purpose the naive bayes classification method to construct the student dropout prediction using naive bayes. This work examines the critical topic of forecasting student dropout rates in higher education using machine learning approaches, with a particular emphasis on the random forest algorithm and the naive bayes algorithm. The study's goal is to properly anticipate dropout rates using data mining methods and machine learning algorithms after conducting a thorough evaluation of existing literature and approaches. The systematic method consists of data collection from a Kaggle dataset, data preparation to solve class imbalance via SMOTE oversampling, and algorithm selection. Random forest and naive Bayes approaches outperform other machine learning algorithms in terms of accuracy, sensitivity, specificity, and precision. The study underscores the importance of considering diverse factors such as demographic data, socioeconomic factors, and academic performance in dropout prediction models. The implications of this research extend beyond academia, with the potential to inform proactive interventions and support systems, ultimately leading to improved student outcomes and institutional effectiveness. According to this paper, the paper outputs that for the binary classification on the data set used in this project has best performed with Naive Bayes and Random Forest Algorithm with SMOTE oversampling. Keywords- SMOTE oversampling, machine learning, Random forest, naive bayes.

Demystifying the Black Box: A Technical Analysis of Transparency Requirements in Clinical AI Systems

This analysis examines the adequacy of Ghana's current regulatory framework in addressing AI explainability in clinical decision support systems. It evaluates existing healthcare laws, derives underlying principles, and assesses their application to AI governance. The study finds significant gaps in the current regulatory regime, including a lack of AI-specific provisions, insufficient explainability requirements, and inadequate frameworks for liability and accountability. While existing principles provide a foundation, they are insufficient to fully address the challenges posed by AI in healthcare. The analysis concludes that comprehensive regulatory development is needed, including AI-specific healthcare regulations, technical standards for explainability, and enhanced regulatory capacity. This study is significant as it provides a roadmap for developing effective AI explainability regulations in Ghana's healthcare sector. It highlights the urgent need for regulatory evolution to ensure safe, ethical, and transparent use of AI in clinical decision support, potentially serving as a model for other developing nations facing similar challenges.

Making the mos(s)t of nature? Cleantech, smart nature-based solutions, and the ‘rendering investable’ of urban moss

This article examines the ways in which ‘nature-based solutions’ (NBS) to urban environmental problems are contributing to a re-imagining of the forms and roles of vegetal life in cities. Specifically, we examine the versions of nature that are being produced within a subset of nature-based solutions described as ‘smart’ – that is, those involving the enrolment of non-human lifeforms into digital infrastructures comprising sensors, data flows and automated support systems. Whilst NBS are often celebrated for opening up cities to lively ecological processes – thereby contributing to more convivial, ‘more-than-human’ forms of urbanism – their smart incarnations are becoming a playground for entrepreneurial and financial actors seeking new ways to enclose, commodify and derive profit from non-human life in cities. To explicate this argument, we examine the case of a proprietary ‘nature-based solution’ to urban air pollution developed and sold to local authorities and corporate actors by a European cleantech start-up, predicated on optimising the air-filtering capacities of moss. Our analysis proceeds in three stages. First, we draw on scholarship on the bioeconomy to show how the commodification of moss in this case is predicated on discursive arguments which depict moss as at once inherently productive and regenerative, but also fragile and scarce in urban environments. Secondly, we show how this smart NBS is rendered investable through the enrolment of moss into a carefully designed digital apparatus, which purports to stabilise and optimise its air purifying work, thereby making its contributions to urban air quality continuous, consistent and calculable. Finally, building on an assessment of the entanglement of this example with specific urban geographies and modes of urban governance, we critically reflect on the role that smart NBS in general might yet play in either reinforcing or disrupting prevailing dynamics of privatisation, enclosure and green gentrification in cities.

A Support System for Street Food Vending: Utilizing Urban Geoinformatics to Facilitate the Relocation of Food Stalls in Bangkok

A Support System for Street Food Vending: Utilizing Urban Geoinformatics to Facilitate the Relocation of Food Stalls in Bangkok

Evaluating the Impact of an AI Critical Friend on Student Research Proposals, Critical AI Literacy, and Transparent Collaborative Assessment Practices

This paper presents a work-in-progress report on an innovative approach to integrating generative AI capabilities into the assessment process, focusing on research proposal development. Specifically, the study explores the impact of incorporating an AI-powered "critical friend" that provides targeted feedback and guidance to students as they craft their research proposals. The aim is to evaluate how this AI-powered support system affects students' critical AI literacy, the quality and transparency of the collaborative assessment process, and, ultimately, the strength of the final research proposals. Through a mixed-methods approach combining surveys, focus groups, and analysis of student work and interactions with generative AI, the researchers seek to uncover key insights on the benefits, challenges, and ethical considerations of leveraging AI to enhance the research proposal development experience. The findings from this study will contribute to the growing body of literature on the role of AI in academic assessments and provide practical recommendations for educators and institutions looking to responsibly integrate these emerging technologies.

Integration of Mental Health Concepts in the Middle School Curriculum

This qualitative study explores the experiences of middle school teachers of Liaocheng Vocational and Technical School with student mental health education within their school setting. Drawing on interviews with teachers, supported interviews with school administrators and parents, the study aims to understand the challenges, resources, and support systems in promoting student well-being that teachers believe would be most beneficial in facilitating effective mental health education. Through a qualitative inquiry, and specifically using purposeful sampling, ten participants will be selected to provide rich insights into the phenomenon. Data will be collected through semi-structured interviews and analyzed using thematic analysis. Results may highlight the multifaceted nature of supporting student mental health, encompassing recognition of mental health issues, role breadth, efficacy in providing support, and barriers faced within the school environment. It is hoped that the study contributes to the literature by offering insights into the complexities of addressing student mental health within the middle school context and informing the development of effective interventions and support systems.

Family Psychological Distress among OFW Parents and their Children in the Middle East: A Mixed Method Study

Aims: This study aims to examine the psychological impact of family separation on Overseas Filipino Workers (OFWs) and their children, with a focus on emotional distress, coping strategies, and the long-term effects of prolonged separation on family dynamics. Sample: The study involved 50 OFW parents residing in Dubai and 50 of their children aged 8-18 living in the Philippines, providing a dual perspective on the experiences of both parents and children. Study Design: A mixed-methods research design was utilized, integrating both quantitative and qualitative approaches to offer a comprehensive understanding of the psychological impacts of family separation. Place and Duration of Study: Data were collected between January and August 2024, with participants recruited through community organizations supporting OFWs in Dubai. Methodology: Quantitative data were collected using the Depression, Anxiety, and Stress Scale (DASS-21) and the Emotional Regulation Questionnaire (ERQ). Semi-structured interviews provided qualitative insights into emotional experiences, coping mechanisms, and the challenges of reintegration. Statistical analyses explored correlations between separation duration, communication frequency, and psychological distress. Results: Quantitative findings from the ANOVA revealed that OFW parents had a significantly higher mean depression score (16.3, SD = 5.4) compared to their children (14.4, SD = 4.2), F (1, 98) = 4.21, p < 0.05. Anxiety levels were similarly elevated in both parents (18.1, SD = 6.2) and children (18.6, SD = 5.7), with no significant difference, F (1, 98) = 0.12, p > 0.05. A positive correlation (p < 0.01) was found between the length of separation (average 3.5 years) and psychological distress. Frequent communication was associated with lower anxiety levels (p < 0.01). Qualitative analysis identified seven key themes: emotional burden of separation, coping strategies, impact on family dynamics, reintegration challenges, mental health and well-being, support systems, and emotional regulation. Parents expressed regret over missing family milestones, while children reported feelings of abandonment. Some families, however, demonstrated resilience through strong communication practices and emotional regulation skills. Conclusion: The study underscores the urgent need for comprehensive mental health interventions that address the psychological challenges experienced by OFW families. Emotional support systems, in addition to financial assistance, are essential to mitigating the emotional toll of prolonged separation and fostering healthier family dynamics.

Актуальные стратегии научно-методического сопровождения педагогических работников как механизм формирования единого образовательного пространства

<p>This publication examines the features of the integration of universities into the system of scientific and methodological support for teaching and HR staff. The most significant areas of activity of scientific and methodological centers for supporting teaching staff, created on the basis of universities, are analyzed to improve the conditions for improving the professional skills of teaching and HR staff. The central issue of discussion is the definition of strategies for the activities of scientific and methodological centers oriented on solving problems within the framework of the formation of a unified educational space in the Russian Federation. Strategies for scientific and methodological support of teaching staff are considered based on the practical experience of universities in implementing educational and scientific projects in accordance with the criteria, which determines the increase of the innovative potential in organizations, the practical significance of the content and forms of scientific and methodological support, the formation of infrastructure for supporting teaching staff, problem specialization and expertise in the activities of scientific and methodological centers, as well as the development of the interaction with professional communities.</p>

Correlational Study on Burnout among University Teachers in Hunan, China

Education is a cornerstone of national development in China, essential for fostering scientific self-reliance and social progress. The 20th National Congress of the Communist Party of China aims to transform the country into a global education powerhouse by 2035, with higher education as its focal point. In this context, Hunan Province, home to various big university in the country, must look into reforms to enhance its educational infrastructure and teacher quality, however, numerous issues also exist including job burnout among teachers. This study investigates burnout among university teachers in Hunan, exploring its prevalence and the factors contributing to it. Utilizing a descriptive-comparative-correlational research design, the study surveyed 300 faculty members across different universities, gathering quantitative data on their demographic profiles, levels of burnout, and perceptions of its causes.This research underscores the urgency of addressing burnout to maintain educational quality and advance Hunan’s educational objectives as findings reveal apparent levels of emotional exhaustion, depersonalization, and decreased personal fulfillment among respondents, with burnout intensity influenced by years of working experience. While no substantial differences in burnout were noted based on profile, perceptions of burnout factors varied by job title and experience, suggesting that institutional roles significantly affect burnout experiences. The study highlights a critical need for targeted interventions to mitigate burnout and enhance faculty well-being, emphasizing the importance of supportive management systems, fair compensation, and robust interpersonal relationships. Recommendations include implementing tailored support programs, improving job satisfaction through clearer feedback and emotional support, and fostering a collaborative work environment to promote professional development.

Evaluation of decision support to wean patients from mechanical ventilation in intensive care: a prospective study reporting clinical and physiological outcomes

AbstractThis study investigated the clinical and physiological response to use of the BEACON Caresystem, a bedside open-loop decision support system providing advice to guide clinicians when weaning patients from invasive mechanical ventilation. Multicenter prospective study conducted in five adult intensive care units in the UK. Following screening and assent, intubated patients mechanically ventilated for > 24 h were randomized to intervention or usual care. Intervention consisted of application of the BEACON Caresystem’s advice on tidal volume/inspiratory pressure, inspired oxygen, respiratory rate and PEEP. Usual care was defined as local clinical practice. The primary outcome was duration of mechanical ventilation. Secondary outcomes quantified prolonged intubation and survival; adverse events; ventilator settings and physiological state; time spent in ventilator modes; links to other therapy; the frequency of advice utilization and time spent outside normal physiological limits. The study was terminated early with a total of 112 patients included. Fifty-four were randomised to the intervention arm and fifty-eight to usual care. The study was underpowered and no significant differences were seen in duration of mechanical ventilation (p = 0.773), prolonged intubation or survival. Intervention arm patients had lower rates of adverse events (p = 0.016), including fewer hypoxaemic events (p = 0.008) and lower values of PEEP (p = 0.030) and tidal volume (p = 0.042). Values of peak inspiratory pressure and pressure support were reduced but at the boarder of statistical significance (p = 0.104, p = 0.093, respectively). No differences were seen for time in ventilator mode or other therapy. Advice presented by the decision support system was applied at the beside an average of 88% of occasions, with a significantly increased number of changes only in inspired oxygen fraction. No significant differences were seen in time spent outside physiological limits. This study investigated the use of the BEACON Caresystem, an open loop clinical decision support system providing advice on ventilator settings. It was terminated early, with no significant difference shown in duration of mechanical ventilation, the primary outcome. Application of advice indicated potential for fewer adverse events and improved physiological status. (Trial registration ClinicalTrials.gov under NCT03249623. Registered 22nd June 2017)

Perinatal Loneliness and Isolation Early in the COVID‐19 Pandemic in New York City: A Qualitative Study

IntroductionDuring the COVID‐19 pandemic, birthing parents were identified as a high‐risk group with greater vulnerability to the harms associated with SARS‐CoV‐2. This led to necessary changes in perinatal health policies but also to experiences of maternal isolation and loneliness, both in hospital settings, due to infection mitigation procedures, and once home, due to social distancing.MethodsIn this study, we qualitatively explored birthing and postpartum experiences in New York City during the early days of the pandemic when lockdowns were in effect and policies and practices were rapidly changing. Using thematic analysis, our focus was on experiences of isolation, navigating these experiences, and the potential impacts of isolation and loneliness on maternal health for 55 birthing people.ResultsParticipants described numerous stressors related to isolation during the birthing process, including reconciling their hopes for their birth with the realities of the unknown and separation from partners, family, and friends in the hospital. During the postpartum period, loneliness manifested as having limited or no contact with family and friends, which led to feelings of a need for strengthened social support systems. The impact of these negative experiences shaped mental health. Overall, we found that solitary experiences during birthing and postpartum isolation were major sources of stress for participants in this study.DiscussionTo support impacted families and prepare for future crisis events, clinicians and researchers must prioritize the development of strong clinical and social support structures for perinatal people to ensure both maternal and child health.

Establishing a biologics and biosimilars committee/network: assessing educational requirements of pharmacy and other healthcare professionals

Abstract Introduction Successful professional networking involves shared, mutually beneficial interactions between individuals and/or individuals and groups1. Biologics and biosimilar medicines prescribing is rapidly evolving with an increasing number of clinical indications in healthcare2,3. Despite their importance, the absence of a structured national network dedicated to these complex therapies has left a gap in professional education and resource sharing among pharmacists. Recognising the necessity for a cohesive support system, this work explores the learning and professional needs of pharmacists regarding biologics and biosimilars and the potential development of a national pharmacy network to address these gaps. Aim The survey aimed to explore the educational needs and preference for a network and/or committee for pharmacy and other healthcare professionals focused on biologics and biosimilars medicines. Methods An electronic survey was developed and deployed for pharmacy and other healthcare professionals involved in the management of biologics and biosimilars via email cascade and social media, 12th February - 6th March 2023. The survey explored the preferred structure of the proposed group; formal committee and/or informal network, what the group would deliver, and any educational needs for members. The survey included questions about the respondent’s roles, sectors of work, regions and their clinical area(s). The open text responses were themed. The NHS health Research Authority tool was used to identify this project as service improvement and development, therefore did not require ethical approval. Results The responses received were from 46 pharmacists, 1 pharmacy technician, 15 doctors and nurses and 4 participants whose roles were unknown, working across multiple sectors; hospital, community, industry, and academia with representation from the devolved nations (n=3) and internationally (n=1). Most respondents expressed a need for a dedicated network and committee n=52 (79%), n=10 (15%) formal network, and n=4 (6%) informal committee. Common themes in response to what the group should deliver and educational needs included; harmonisation of approaches to guidelines and policies, pathway design, reduction in unwarranted variation (68%); platform to share new ideas, knowledge and peer advice (44%); strategy and leadership in service delivery and promotion of best practice and cost training, horizon scanning (29%); working collaboratively to produce multi-centre research projects (24%); to create a structured training programme for health care professionals (9%). Discussion/Conclusion The survey results highlight a gap in the current educational and professional support systems for PP’s concerning biologics and biosimilar medicines. The identified learning needs point to a strong demand for a structured network that can provide targeted education, share best practices and facilitate professional networking. The expertise within the group can also create formal eLearning programmes for healthcare professionals. This work serves as a foundational step towards the development this network, highlighting the critical areas of focus and the collective interest of the pharmacy community in bridging these gaps. The network should also facilitate communication and collaboration across different sectors, fostering a more cohesive and informed pharmacy community. Such an innovative network would not only enhance individual competency but also contribute to the overall advancement of pharmaceutical care in this specialised area.

The reaction of the social security systems of the European Union and the united states of America to financial crises: proposals for using the experience in Russia

In the context of accelerated transformation of the domestic economy, attempts at economic and socio-political isolation of the Russian Federation (hereinafter referred to as RF, Russia), the question of rethinking the role of social protection in the development of the RF arises. The purpose of the work is to develop recommendations for increasing the adaptability of the domestic social protection system to future possible shocks, with consideration to modern practices used in developed economies. The object of the study is social protection systems. The subject is measures of adaption of these systems to consequences of financial crises. When conducting the study, the following methods have been used: analysis, induction, measurement, comparison, computational and constructive, statistical and economic. The main results of the study include identification of the basic channels for the transition of a financial crisis into a social one, and assessment of the fiscal impulses of the European Union countries, United States of America, and Russia in order to mitigate the negative shocks of financial crises. The practical significance of the work is due to the possibility of using the results in the activities of government bodies as part of improving the domestic social protection system. The similar nature of consequences of global financial crises has allowed us to draw a number of conclusions. Firstly, job retention schemes and social support measures for the unemployed population make it possible to create an effective system of income support for workers, especially for vulnerable groups. Secondly, increasing the targeting of social support measures will lead to the performance growth of social protection system, allowing for a more rational distribution of limited budget resources. Finally, this social system can effectively reach the target segment of beneficiaries only if means-testing information systems are of high quality.

An exploratory analysis of repeat victimisation of domestic violence disclosure scheme applicants

ABSTRACT This study explores the impact of the Domestic Violence Disclosure Scheme (DVDS) on repeat victimisation among applicants. By analysing all ‘Right to Ask’ applications to Avon & Somerset Constabulary in 2021, the study investigates the extent of prior domestic abuse victimisation and the influence of disclosure decisions on subsequent reports. The findings reveal that 80% of applicants had prior victimisation records, and disclosures were made in 53% of the cases. The probability of subsequent abuse reports increased significantly for those with prior victimisation when disclosures were made, highlighting the need for robust support mechanisms post-disclosure. The study complements debate around the theoretical tension between empowerment and responsibilisation within DVDS and calls for enhanced support systems and rigorous outcome evaluations. These results suggest that while DVDS aims to protect victims, its effectiveness in reducing victimisation requires further empirical validation and comprehensive support strategies.

Evolution of support policies for the development of distant-water fishing bases in China: Review, performance, challenges and prospects

Distant-water fishing bases are an important carrier and development platform for the development of distant-water fishing. It is necessary to analyze the evolution of the policies supporting offshore fishing bases in order to promote the standardized and orderly development of distant-water fisheries. Based on 302 policy documents, this paper adopts the content analysis method to analyze the policies since 1993 using ROSTCM6 software. These policies can be divided into three phases: the start-up period (1993–2010), the rapid development period (2011–2015) and the steady development period (2016–2023). The study found that the interrelationship and complementarity between fishing base-focused and related policies have increased, with continuous improvements in the policy framework, a shift toward developing a green and healthy industry chain, and an expanded scope of policy support. However, there are still some limitations in the evolution of support policies for the development of distant-water fishing bases, including an imperfect industrial support system, insufficient talent reserves and inadequate management policies. Finally, the paper emphasizes the need to improve the policy system, promote the development of the whole industry chain of distant-water fisheries, build a talent training system, strengthen scope and capacity of international cooperation in distant-water fisheries, promote the sustainable development of fisheries and enhancing international compliance capacity.

Enhanced Fuzzy Score-Based Decision Support System for Early Stroke Prediction

According to the Global Health Observatory (GHO), stroke ranks second worldwide in causing dementia, right after Alzheimer's disease. The mortality rate linked to dementia resulting from stroke is high because symptoms are often recognized late, and stroke can be misinterpreted as other brain disorders. Early detection and diagnosis of stroke is crucial. Therefore, increasing awareness of stroke symptoms and implementing preventive measures becomes imperative. Prompt intervention by healthcare professionals can improve outcomes and reduce long-term complications of stroke. The research introduces an innovative approach for early stroke prediction using a fuzzy scoring-based Decision Support System. This approach encompasses three main modules: Mind-map based Data Modeling, Fuzzy scoring computing, and ML-based Decision System. By incorporating fuzzy logic, the approach extracts valuable knowledge from imprecise and uncertain data. Combining the fuzzy stroke risk model with a machine learning-based decision support system aims to enhance stroke prediction accuracy and improve preventive measures and patient outcomes. The approach's effectiveness was validated using real clinical data and tested with various machine learning classifiers, including K-Nearest Neighbour (KNN), Logistic Regression (LR), Decision Tree (DT), Artificial Neural Network (ANN), and Support Vector Machine (SVM). The results showed a strong correlation between stroke cases and computed risk-scoring values. In comparison to predictions without fuzzy scoring and other related works, the stroke risk prediction using the proposed approach demonstrated higher accuracy, making it a promising method for early stroke detection and prevention.

Accounting Information Systems and Performance of Manufacturing Companies in Rwanda. Case of CIMERWA Plc

Purpose: The general objective of this study was to assess the effect of Accounting Information Systems (AIS) on the performance of manufacturing companies in Rwanda, focusing on a case study of CIMERWA Plc. Specifically, the study assessed the effect of Accounting Information Systems security on the performance of CIMERWA Plc, examined the effect of Accounting Information Systems accuracy on the performance of CIMERWA Plc and analysed the effect of Accounting Information Systems reliability on the performance of CIMERWA Plc. Methodology: The study was descriptive as well as correlational. A population of 157 from various departments within CIMERWA Plc. A sample size of 113 was determined by the researcher using Slovin's formula. Every member of the population has an equal chance of getting chosen when a simple random sampling is used. Questionnaire and interview guide all played a role in the data collection process. Within the scope of the research, SPSS 25 was used. Findings: The results indicate coefficient for AIS security is 0.307, suggesting that for each unit increase in AIS security, performance improves by 0.307 units, with this relationship being statistically significant. Similarly, the coefficient for AIS accuracy is 0.323, indicating that a one-unit increase in AIS accuracy corresponds to a 0.323 increase in performance, which is also statistically significant. Additionally, the coefficient for AIS reliability is 0.348, signifying those improvements in AIS reliability enhance performance by 0.348 units, with a statistically significant impact. Unique Contribution to Theory, Practice and Policy: The study recommends that CIMERWA PLC enhance AIS security through multi-factor authentication, employee training, and advanced technologies; improve AIS accuracy via audits, automated validation, and staff training; and strengthen AIS reliability through regular updates, user support systems, and feedback mechanisms to ensure seamless operations and optimal data management.