Issue Resolution Research Articles

IoT and AI for Real-time Water Monitoring and Leak Detection

Water is essential for ecological sustainability and human survival, necessitating effective management to meet rising global demands and address climate change. Traditional water supply monitoring methods are labor-intensive and slow, limiting real-time data acquisition and issue resolution. This paper presents QoW-Pro, an IoT-based water monitoring system that leverages AI algorithms to significantly enhance water quality assessments and leak detection. QoW-Pro enables real-time data collection, predictive modeling, and anomaly detection, leading to improved decision-making in water resource management. The system demonstrates quantitative improvements in leak detection accuracy and water quality prediction, offering a scalable solution adaptable to both urban and agricultural settings. By combining IoT and AI, this research contributes to the sustainable management of water resources, ensuring their availability and quality for future generations.

An Intelligent Approach to Data Quality Management AI-Powered Quality Monitoring in Analytics

This study explores an intelligent approach to data quality management using AI-powered quality monitoring systems. Traditional data quality processes often rely on manual interventions, which are time-consuming, error-prone, and incapable of handling the increasing volume and complexity of modern datasets. AI-driven solutions address these limitations by leveraging machine learning, automation, and anomaly detection to continuously monitor, towards detect inconsistencies, inaccuracies, and missing values across data pipelines. AI-powered systems not only ensure data integrity but also optimize data processing workflows, reducing the need for human oversight. Additionally, automated monitoring provides actionable insights for proactive issue resolution, thereby improving overall data governance and analytical outcomes. This paper highlights the benefits of implementing AI-based quality monitoring, including improved accuracy, scalability, and efficiency in data management processes. The study concludes that AI-powered data quality management is a transformative solution for businesses seeking to maintain high-quality data in a dynamic and complex analytics landscape. Accurate analytics and successful decision-making in today's data-driven economy depend on ensuring data quality. An insightful method for managing data quality using quality monitoring systems driven by AI is presented in this paper. Automated statistics cleansing, anomaly detection, and real-time consistency assurance are three ways in which AI-driven solutions tackle these problems. A.I. improves data correctness, finds mistakes, gets rid of duplicates, and fills in gaps in datasets by using machine learning algorithms, predictive analytics, and anomaly detection methods. In addition, AI systems keep a close eye on data pipelines, offering insights and solutions to prevent data breaches in real time. Data management scalability, efficiency, and dependability are all enhanced by this method, which also decreases the need for human involvement. The results show that analytics systems are much improved with AI-powered data quality management, which helps businesses get better insights and make better choices. We can get high-quality data, optimised processes, and enhanced analytical findings by incorporating AI into data quality frameworks, according to this research

BlockGuard: Advancing digital copyright integrity with blockchain technique

In the swiftly advancing media sector, piracy remains a significant challenge, eroding consumer willingness to pay, undermining rightful economic gains for copyright holders, and diluting creative incentives for content creators. Existing copyright protection mechanisms are inadequate for robust intellectual property safeguarding within complex digital environments, especially lacking in lifecycle tracking, authenticity verification, and dispute resolution. This paper introduces BlockGuard, a pioneering blockchain-based credible digital copyright management system designed to mitigate these issues through strategic use of blockchain and digital watermarking techniques. Furthermore, it enhances issue resolution via the application of Non-Fungible Token (NFT) contracts. BlockGuard aims to achieve three primary objectives. Firstly, it enables comprehensive lifecycle tracking of digital assets, ensuring visibility from content creation to its diverse applications. Secondly, by employing digital watermarking, it provides stringent authenticity verification to drastically reduce copyright infringements. Lastly, leveraging blockchain’s immutability and transparency, it streamlines dispute resolution processes. BlockGuard presents an efficient, secure, and transparent approach for managing digital copyrights in today’s media landscape. It showcases a detailed protection center and public appraisal workflow, and verifies the effectiveness of three originality detection processes. In terms of performance, BlockGuard requires 88% of the storage space on secondary storage compared to conventional solutions (that store only the original image) and incurs minimal storage overhead at the kilobyte level on blockchain storage. Furthermore, its most resource-intensive operation consumes no more than 200,000 gas, with other operations requiring no more than 100,000 gas, equivalent to a standard Ethereum transaction.

Investigating the e-learning choice under the learners’ perspective using demand driven learning model: insights from Vietnam

Over the past four decades, e-learning has experienced rapid global growth, revolutionizing higher education. In Vietnam, universities have increasingly turned their attention and resources toward e-learning development, adapting to specific contexts and needs. This study investigates the drivers of e-learning choice within the framework of the demand-driven learning model (DDLM), with a primary focus on three core factors: quality content, delivery, and service. Employing a quantitative approach and the PLS-SEM technique, this research uncovers significant findings. The results of the study highlight the pivotal role of quality content, which exerts the most potent influence on e-learning choice, evidenced by a robust path coefficient of 0.400. Service and delivery, with direct path coefficients of 0.183 and 0.173, respectively, also play substantial roles in shaping e-learning decisions. Moreover, mediate role of delivery in the the e-learning choice model has been confirmed. Quality content leads to delivery, and delivery, in turn, leads to e-learning choice. Similar pathway has been found with service. A higher level of service increases delivery, which positively impacts on e-learning choice. These findings hold critical implications for the formulation of e-learning development policies in Vietnam’s higher education institutions. Universities should prioritize the continuous development of high-quality, engaging, and up-to-date educational content that aligns with industry needs and student interests. Additionally, emphasis should be placed on providing a supportive e-learning experience, characterized by responsive customer service, accessible technical support, and efficient issue resolution mechanisms. Moreover, universities should consider the implementation of user-friendly and interactive content delivery platforms and methods that actively engage learners. In essence, this research serves as a guide for universities in Vietnam, enabling them to enhance their e-learning offerings by ensuring the content quality, support services, and delivery methods, ultimately fostering a dynamic and accessible learning environment that meets the evolving needs of their students and the demands of the modern educational landscape.

Exploring Faculty Members’ Experiences with Virtual Classroom Platforms and Their Perceived Usability during the COVID-19

This two-phase mixed-method study examined faculty experiences with Virtual Communication Platforms (VCPs) and their usability in distance education during the COVID-19 epidemic. A stratified random sample of 913 faculty members from 167 universities was selected to participate in an online questionnaire that included the System Usability Scale, demographic information, and open-ended questions. Twenty-five of the faculty members who had completed the online questionnaire were then interviewed in semi-structured interviews. The quantitative analysis results indicate that Zoom was the most favored platform, obtaining a ‘Good’ usability score together with Google Meet and Adobe Connect. In contrast, Perculus and Microsoft Teams were evaluated as having ‘Poor’ usability. Results also revealed the significant effect of gender on Perculus, distance education experience on Zoom, and age and academic status on Zoom and Google Meet usability perceptions. Furthermore, the qualitative analysis results revealed usability challenges (e.g., technical challenges, functionality issues, usability concerns), positive aspects (e.g., usability and effectiveness, support and issue resolution, performance and accessibility), and suggestions for improvement (e.g., instruction and support, exploration and optimization, format and assessment enhancement). The study offers valuable insights for institutions to make informed decisions about adopting VCP, investing in targeted training programs, and ultimately fostering a more effective and inclusive distance education environment.

A-133 Trusted Test Goes Awry: Investigating Dilution Aberrations for Total Bilirubin

Abstract Background A patient with acute decompensated cirrhosis was hospitalized due to lightheadedness and jaundice, undergoing evaluation for a liver transplant. The attending physician brought to the laboratory’s attention a perplexing pattern in the patient's total bilirubin results. Initially, the patient displayed a consistent trend of elevated total bilirubin levels above the upper limit of linearity, ULOL (> 30 mg/dL), which then plummeted to under the limit of quantification (< 0.1 mg/dL) before surging back to > 30 mg/dL. Methods The total bilirubin in heparinized plasma was measured on the AU5800 by Beckman Coulter. Samples > ULOL are diluted automatically 1:3 utilizing the instrument’s on-board dilution feature. The final test results are reported automatically to an electronic medical record. Following the reported incident, an investigation and troubleshooting plan was developed, encompassing the following steps: Repeat patient testing with total bilirubin concentration > 30 mg/dL and <0.1 mg/dL; Rule out the previously reported potential interferences, including Immunoglobin M and acetaminophen; Conduct a 90-day quality control (QC) review; Perform split test analysis on two instruments within the laboratory and at a reference laboratory; Conduct patient chart reviews to identify discrepancies based on previously reported values; Complete a root cause analysis and develop corrective/preventive action plan. Results Patient sample < 0.1 mg/dL was tested on an alternative instrument, resulting > 30 mg/dL. Patient with normal IgM of 161 mg/dL didn’t reveal any other potential drug interferences in chart review. The 3-month QC review found consistent with peer performance. Split comparison of 6 patients revealed discrepancies for samples > 30 mg/dL on one of the two instrument units. When total bilirubin > 30 mg/dL, the malfunctioning unit erroneously reported values < 0.1 mg/dL after dilution. Review of 34 patient charts showed the impact dates were spanned for 39 days. Since the on-board dilution feature is utilized by 10 other analytes, 892 diluted samples were analyzed for discrepancies. 36 discrepant results were identified among 4 affected assays including total bilirubin, direct bilirubin, creatine kinase, and alanine aminotransferase. These results were corrected, and providers were notified. Conclusions The root cause was traced to a malfunction in one instrument unit, despite no malfunction flags. The laboratory QC concentrations fell within the analytical measurement range, missing the dilution issue during the daily QCs. During an extensive repair period, the on-board dilution was disabled on the affected unit and samples were re-routed to alternative instrument for testing. Policy changes and operator training were initiated for a new result verification process, impacting the laboratory productivity. Autoverification of diluted sample results was disabled for all chemistry analyzers. The vendor identified the issue as sample transfer unit crane misalignment in the up/down direction. It is worth noting that proficiency testing or QCs often do not extend beyond the analytical measurement ranges, leading to undetected incidents. Additional quality measures like periodic patient chart reviews, patient sample comparisons, and other quality assurance tools can aid in on-going dilution performance verification. Open communication between the physicians and laboratories is crucial for prompt issue identification and resolution.

The Role of Business Analysts in Optimizing HCM Systems: A Study of Post-Implementation Support Effectiveness

Abstract: This article investigates the effectiveness of Business Analysts (BAs) in the post-implementation phase of Human Capital Management (HCM) systems, aiming to develop a comprehensive framework for measuring BA performance and its impact on system optimization and user satisfaction. Employing a mixed-methods approach, the article combines quantitative analysis of key performance indicators (KPIs) such as response time, issue resolution rate, and system performance metrics with qualitative insights from case studies and user surveys. The article examines 150 BAs across 25 organizations, revealing that BAs who effectively balance technical expertise with strong communication skills contribute significantly to sustained HCM system success. Findings indicate that proactive BA involvement in user training and continuous system improvement correlates with a 30% increase in user satisfaction and a 25% reduction in system-related issues. The article culminates in a novel effectiveness measurement framework and recommendations for enhancing BA performance in post-implementation support, offering valuable insights for organizations seeking to optimize their HCM systems and maximize the value of their BA roles.

Digital twin-enabled quality control through deep learning in industry 4.0: a framework for enhancing manufacturing performance

ABSTRACT In the context of Industry 4.0, integrating Digital Twin (DT) technology stands out as a critical challenge for enhancing manufacturing processes and productivity. The combination of DT and Artificial Intelligence (AI) provides a significant benefit for improving processes in real-time. Industries are actively researching these technologies to keep pace with the rapid evolution of technology, utilizing virtual representations for efficient real-time monitoring and control. The present paper proposes a new approach that relies on DT technology for monitoring, optimizing manufacturing processes and enabling quality control through Deep learning (DL). The proposed methodology involves creating a digital replica of the physical system and utilizing DL models for quality control purposes. This approach improves automation and productivity while maintaining high levels of quality assurance in factories. DL is deployed within the DT for gathering data from the physical system and making predictions regarding product quality. The approach is illustrated by considering an experimental industrial prototype. The results obtained are particularly intriguing, demonstrating heightened predictive accuracy in assessing product quality and real-time issue resolution. Overall, the findings underscore the significant and interesting impact of DT technology with DL on manufacturing processes in the context of Industry 4.0.

Artificial Intelligence Implementation in Agile Project Management Addressing Challenges and Maximizing Impact

The Agile methodology, with an 80% adoption rate, often faces challenges leading to project failures. This study investigates using artificial intelligence (AI) to overcome these challenges through a systematic literature review of 44 papers. It examines AI's impact on key Agile phases: envision, speculate, explore, adapt, and close. Findings highlight AI's critical role in improving project outcomes by addressing implementation challenges. AI tools aid in risk assessment and project selection during planning, enhance effort estimation and task allocation in speculation, improve team communication and technical issue resolution in exploration, optimize systems in adaptation, and provide valuable insights in closure. The paper offers guidance on effective AI integration to enhance Agile Project Management success.

Boosting Financial Audits with AI: Insights from Auditors at Public Accounting Firms Affiliated with OAI Solusi Manajemen Nusantara

The integration of artificial intelligence (AI) into auditing practices promises to revolutionize the profession by enhancing efficiency, accuracy, and insight. This study investigates AI's impact on 150 auditors from OAI Solusi Manajemen Nusantara member firms across Indonesia, utilizing a Google Form survey. AI automates tasks such as data collection, reconciliation, anomaly detection, and risk assessment, allowing auditors to focus on high-value activities like fraud detection and generating actionable insights. Continuous auditing enabled by AI ensures timely issue detection and resolution, improving transparency and stakeholder communication through more informative audit reports. Challenges include ensuring data quality and understanding AI model outputs, critical for auditors to effectively interpret and trust AI-driven recommendations.

Assessing the Impact of Public Accounts Committee (PAC) Reports on Government Accountability

This study examines the effectiveness of the Public Accounts Committee (PAC) in Malaysia to enrich the understanding of its role in promoting governmental accountability. Through an extensive content analysis of the PAC reports spanning from 2019 to 2022 sourced from the Official Web of Parliament PAC, issues raised by the PAC were categorized into key improvement areas. Findings unveiled 104 flagged issues, with 68 addressed effectively, while 29 remained unresolved despite agreements for action and 7 lacking government response. The government's consideration of 97 out of 104 issues, reflecting a response rate exceeding 90%, underscored the PAC's pivotal role in fostering accountability. This study presents a comprehensive analysis of the prevailing issues identified in PAC reports and their current resolution status. It offers crucial insights for legislators to enhance the efficacy of their oversight procedures. Additionally, it provides empirical data on the impact of legislative oversight on governmental operations. The findings highlight the PAC's capacity to instigate positive reforms within government agencies, thereby enhancing transparency and promoting accountable governance. Future research should explore how the composition of the PAC committees influences issue resolution and government responses, while further investigations are recommended to evaluate the effects of the PAC recommendations on governmental practices.

Unveiling the Veil: Gender Differences in Satisfaction among K12 Teachers in the Teacher Activity Groups Initiative

This study aimed to investigate the influence of gender on the satisfaction of Vietnamese K-12 teachers who participated in Teaching Activity Groups (TAGs), a collaborative professional development (PD) initiative. Using a quantitative approach, questionnaire data was collected from a purposive sample of 147 teachers (108 females, 39 males). The data were subjected to descriptive statistical analysis and Independent Sample t-tests to discern potential gender-based differences in teachers’ satisfaction with TAGs and their perceived impact on teachers’ PD. The results revealed nuanced disparities in satisfaction levels between female and male participants, with generally higher satisfaction levels exhibited by females. Notable areas of difference included knowledge acquisition, skills acquisition, school support, and issue resolution. These areas were indeed discussed in the content, providing a detailed analysis of where gender differences in satisfaction were most pronounced. The results underscore the relevance of gender considerations in PD studies and offer insights for policy and practice in the Vietnamese educational landscape. The study concludes by highlighting the need for further research to explore these gender dynamics and their underlying causes in greater depth.

CHAT MARKETING'S IMPACT ON CUSTOMER SUPPORT SATISFACTION IN FINANCIAL STARTUPS

The subject of this paper is the influence of chat marketing on customer support satisfaction. The purpose of the study is to determine the relationship between the use of chat marketing and customer support satisfaction, as well as to identify the essential factors that contribute to this relationship. Furthermore, this paper aims to provide theoretical insights into the influence of chat marketing on customer support satisfaction in financial startups. Many companies struggle to achieve the most efficient chat session and are uncertain about the best strategies, factors and types of chat to implement. Therefore, these findings will help financial startups to theoretically understand the aspects of chat marketing and customer support satisfaction. The object of this article is the impact of chat marketing on customer satisfaction, and the purpose is to reveal theoretical knowledge that will help identify the factors that contribute to chat marketing and customer satisfaction in financial startups. This paper discusses the importance of customer support for financial startups and the different approaches to providing customer support through emotional means. In addition, this paper highlights the importance of customer satisfaction through trust and commitment to build a positive relationship with the customer. Furthermore, this paper demonstrated the framework behind chat marketing, which includes the use of different tools such as live chat platforms, chatbots and live agents or human representatives that help to achieve customer satisfaction through customer support. Moreover, using methods such as: observation, survey and regression analysis, this paper has demonstrated the importance of customer centricity in the financial sector to provide key essentials for employees as incentives that maintain customer satisfaction, while ensuring the flexibility of real-time communication with chatbots or live agents, with the need to have the ease of use and flexibility and various other factors to contribute to customer support satisfaction. As a result, the paper emphasises that in order to increase customer satisfaction with financial start-ups, it is crucial to maintain a low response rate by providing fast and reliable customer assistance. Developing and regularly updating chatbots to facilitate smooth transitions to live agents in complex situations is essential. Implementing an effective ticketing system to automate and monitor issue resolution is essential, with a focus on resolving issues during chat interactions whenever possible. Adopting a hybrid strategy that combines live agents and chatbots helps to meet diverse customer needs in a timely manner. Investing in comprehensive training for live agents is necessary to ensure professional and timely service. In addition, continuous monitoring and analysis of customer feedback plays a key role in improving overall business performance.

Transformers and meta-tokenization in sentiment analysis for software engineering

Sentiment analysis has been used to study aspects of software engineering, such as issue resolution, toxicity, and self-admitted technical debt. To address the peculiarities of software engineering texts, sentiment analysis tools often consider the specific technical lingo practitioners use. To further improve the application of sentiment analysis, there have been two recommendations: Using pre-trained transformer models to classify sentiment and replacing non-natural language elements with meta-tokens. In this work, we benchmark five different sentiment analysis tools (two pre-trained transformer models and three machine learning tools) on 2 gold-standard sentiment analysis datasets. We find that pre-trained transformers outperform the best machine learning tool on only one of the two datasets, and that even on that dataset the performance difference is a few percentage points. Therefore, we recommend that software engineering researchers should not just consider predictive performance when selecting a sentiment analysis tool because the best-performing sentiment analysis tools perform very similarly to each other (within 4 percentage points). Meanwhile, we find that meta-tokenization does not improve the predictive performance of sentiment analysis tools. Both of our findings can be used by software engineering researchers who seek to apply sentiment analysis tools to software engineering data.

Sustainable Evolution: Investigating the Factors Contributing to the Transformation of Coffee Businesses from Unplanned to Well-Planned, Sustainable Enterprises in Padang

This research aims to identify the factors contributing to the sustainable evolution of coffee businesses in Padang, West Sumatra. The research is an exploratory qualitative study. Each coffee shop, while differing in focus and approach, prioritizes quality, utilizes technology, and implements strategies for long-term sustainability in its operations. Each coffee shop demonstrates unique strategies in outbound logistics, whether through distribution methods, technology integration, strategic cooperation, or customer engagement, tailored to its specific business model and target audience. Each coffee shop employs unique marketing and sales strategies tailored to its business model and target audience, emphasizing customer engagement, promotional diversity, and long-term relationship building. Each coffee shop offers unique services, focusing on customer experience, atmosphere, personalized interactions, and proactive issue resolution to build strong customer relationships and foster loyalty. Each coffee shop employs distinct procurement strategies tailored to its business model and goals, focusing on supplier relationships, diversification, and preparedness for uncertainties to ensure smooth operations and long-term sustainability. Each coffee shop employs structured mentoring, technology integration, and maintenance practices tailored to support long-term sustainability and business growth, ensuring efficient operations and a positive environmental and community impact. Each coffee shop employs structured recruitment, training, and development programs tailored to their business needs, emphasizing employee skill enhancement, performance improvement, and continuous learning to provide excellent service. Each coffee shop employs technology as a tool to enhance sustainability, efficiency, and productivity, utilizing strategies tailored to their specific needs and challenges, whether it’s overcoming network interference, ensuring reliable technology selection, or managing repair costs efficiently.

Emoji Promotes Developer Participation and Issue Resolution on GitHub

Emoji Promotes Developer Participation and Issue Resolution on GitHub

Agent Based Intelligent System for Enhanced Teamwork Performance

It is impossible to overstate the necessity of a strategic and practical approach in the workplace in order to maximize productivity these days. Teamwork is one of the best ways to adapt to the changes that have occurred in today's environment throughout time. In every industry, the optimum performance arrangement for realizing visions, carrying out plans, and accomplishing objectives is teamwork. It is also one of the most crucial components of systems for continuous improvement since it makes information exchange, issue resolution, and the growth of employee accountability easier. Teams function as a grouping of people with complementary talents who work together rather than against one another. They are held accountable for their strategic methods and use them to achieve a shared objective. The Supervised Learning technique was used in this work to simulate team performance utilizing an intelligent coaching agent. Through the use of an automated performance assessment and weighted scores for each task, this study was able to create a system that will remove biases from performance evaluation. As soon as a worker does the task, they will obtain a score. The purpose of this study was to demonstrate an event-based performance approach by developing and utilizing an intelligent coaching agent in a supervised learning team training framework. The goal was successfully met, and the result shows positive impacts on the team's performance.

Nexikon Society (Society Management System)

The “The Nexikon Society” is an offers an integrated platform aimed at facilitating effective communication, information sharing, and issue resolution within residential communities. This platform serves as a centralized hub where society members can access real-time updates, notices, and event announcements, fostering a stronger sense of community engagement and collaboration. Through the Nexikon website, residents have easy access to various community-related information, including updates on ongoing projects, upcoming events, and important notices. Additionally, the platform allows members to view profiles of their neighbour’s, facilitating networking and social interactions within the community. A significant feature of Nexikon is its complaint management system, which enables members to report issues or concerns pertaining to the society. This feature ensures that grievances are addressed promptly and promotes transparency and accountability among society administrators. Moreover, the website restricts database modification privileges to the administrator, ensuring the integrity and security of the data. The administrator is tasked with managing member information, overseeing platform operations, and performing essential tasks to ensure its smooth functioning. Keywords— Society Management System, Residential Communities, Communication, Information Dissemination, Issue Resolution, Administrator, Database Management.

IVOMS: Instrumented Vestibular / Ocular motor screen in healthy controls and mild traumatic brain injury

Objective Vestibular/ocular deficits occur with mild traumatic brain injury (mTBI). The vestibular/ocular motor screening (VOMS) tool is used to assess individuals post-mTBI, which primarily relies upon subjective self-reported symptoms. Instrumenting the VOMS (iVOMS) with technology may allow for more objective assessment post-mTBI, which reflects actual task performance. This study aimed to validate the iVOMS analytically and clinically in mTBI and controls.Methods Seventy-nine people with sub-acute mTBI (<12 weeks post-injury) and forty-four healthy control participants performed the VOMS whilst wearing a mobile eye-tracking on a one-off visit. People with mTBI were included if they were within 12 weeks of a physician diagnosis. Participants were excluded if they had any musculoskeletal, neurological or sensory deficits which could explain dysfunction. A series of custom-made eye tracking algorithms were used to assess recorded eye-movements.Results The iVOMS was analytically valid compared to the reference (ICC2,1 0.85–0.99) in mTBI and controls. The iVOMS outcomes were clinically valid as there were significant differences between groups for convergence, vertical saccades, smooth pursuit, vestibular ocular reflex and visual motion sensitivity outcomes. However, there was no significant relationship between iVOMS outcomes and self-reported symptoms.Conclusion The iVOMS is analytically and clinically valid in mTBI and controls, but further work is required to examine the sensitivity of iVOMS outcomes across the mTBI spectrum. Findings also highlighted that symptom and physiological issue resolution post-mTBI may not coincide and relationships need further examination.

'I think we could probably do more': an interview study to explore community pharmacists' experiences and perspectives of frailty and optimising medicines use in frail older adults.

Community pharmacists potentially have an important role to play in identification of frailty and delivery of interventions to optimise medicines use for frail older adults. However, little is known about their knowledge or views about this role. To explore community pharmacists' knowledge of frailty and assessment, experiences and contact with frail older adults, and perceptions of their role in optimising medicines use for this population. Semi-structured interviews conducted between March and December 2020 with 15 community pharmacists in Northern Ireland. Interviews were transcribed verbatim and analysed thematically. Three broad themes were generated from the data. The first, 'awareness and understanding of frailty', highlighted gaps in community pharmacists' knowledge regarding presentation and identification of frailty and their reluctance to broach potentially challenging conversations with frail older patients. Within the second theme, 'problem-solving and supporting medication use', community pharmacists felt a large part of their role was to resolve medicines-related issues for frail older adults through collaboration with other primary healthcare professionals but feedback on the outcome was often not provided upon issue resolution. The third theme, 'seizing opportunities in primary care to enhance pharmaceutical care provision for frail older adults', identified areas for further development of the community pharmacist role. This study has provided an understanding of the views and experiences of community pharmacists about frailty. Community pharmacists' knowledge deficits about frailty must be addressed and their communication skills enhanced so they may confidently initiate conversations about frailty and medicines use with older adults.