Relevant User Research Articles

From Sales Strategies to Information Ecosystems: The Role of Personalized Recommendation

The paper is about the application of personalized recommendations on online shopping applications to improve sales success and the spread of fake news on social media platforms. First, the paper introduces a personalized recommendation system's concept and working principle, then emphasizes its importance in improving user experience and sales efficiency. Then it analyzes the information cocoon effect that personalized recommendation may bring, it is users only see the content that conforms to their interests and views, which intensifies the single and misleading information. This is followed by a discussion of how companies can use personalized advertisement recommendations to improve sales success.Then through deep learning and search, personalization systems can efficiently provide personalized product recommendations to users, but there are still opportunities to improve their effectiveness, such as improving network effects among relevant users. Therefore, it points out a new method to improve the sales success rate of online shopping applications. Then discusses the role of social networks in the spread of fake news. Finally, through the network diagram, the phenomenon of information-closed loop between different groups is demonstrated, and the information transmission gap that may be caused by personalized recommendations is explained.

Research On Marvel's Marketing Model: An Analysis of Digital Marketing and Synergistic Effect

Marvel Studios occupies a significant position in the global entertainment industry. Its success is attributed not only to its film content but also to its unique marketing strategies. This paper aims to analyze Marvel's digital marketing model and the synergistic effects across different media. Through case studies of Marvel Studios' marketing strategies, this paper explores its practices and achievements in social media, content marketing, and cross-platform collaboration. Furthermore, this paper examines relevant market data and user feedback, comparing Marvel's marketing model with other well-known brands through comparative analysis. The research finds that Marvel has successfully established a strong brand influence and a loyal fan base through precise digital marketing and efficient media synergy. This paper will help other enterprises understand how to use digital marketing and synergies to enhance brand value and market competitiveness, demonstrating the effectiveness of Marvel's digital marketing strategies in developing brand cohesion and achieving high returns.

대학생의 학습양식 기반 학습전략 향상 모바일 앱 프로토타입 개발

Objectives This study aimed to develop a prototype of a mobile application to support the improvement of learning strategies for college students based on their learning styles. Methods With reference to a literature review of learning strategies and styles, strategies were extracted to inform the design of a mobile application aimed at supporting the use of learning strategies based on learning styles. Experts validated the extracted strategies, and the prototype was initially developed accordingly. A usability test was performed with students from University A, and based on the test results, the initial prototype was revised until an evolved version was finalized and presented. Results The strategies were extracted and divided into groups considering such factors as the characteristics of college student users, the connection between learning strategies and academic performance, and the characteristics of mobile applications, respectively. Expert validation of the design strategies indicated that both CVI and IRA were 1.00, securing validity and reliability. The mobile app prototype developed based on the extracted strategies featured menus such as learning style diagnosis, learning strategy recommendation, learning strategy application, learning management, sharing for collaborative learning, and gamification for facilitating learning. The usability test results for the prototype showed that the mean values for all items were 4.25 or higher, signifying positive results. Conclusions The significance of the mobile app prototype presented in this paper lies in its consideration of users’ learning styles, which are among the relevant user characteristics, to recommend appropriate learning strategies and support users as they apply those learning strategies in reality. The study results indicate that utilizing learning styles and gamification could positively influence college students by motivating them to enhance their understanding of learning strategies while also improving their ability to utilize those learning strategies.

Healthcare Provision for the LGBT Community: A Scoping Review of Service Providers and User Perspectives

Objective: This scoping review aimed to explore available literature on the knowledge, attitudes, and practices of healthcare professionals on providing care to the lesbian, gay, bisexual, or transgender (LGBT) community as well as the experiences and perspectives of the LGBT community on their healthcare. Material and Methods: The following electronic databases were searched in December 2020: MEDLINE/PubMed, CINAHL, Web of Science, ProQuest, SCOPUS, and Embase for English-language publications; from 2010 to 2020.Results: This review included 59 studies that were selected from 5,318 studies. This review revealed that there was an increase in publications regarding this topic across the world. This review identified four themes: (I) the current healthcare landscape for the LGBT community, (II) facilitators of and (III) barriers to healthcare access and utilization among the LGBT community, and (IV) varied facets of healthcare of relevance for LGBT healthcare users – communication, space, education and training, research, and policies.Conclusion: This review serves as a valuable compass for future researchers seeking areas for deeper exploration and understanding. Nevertheless, the limitations of the study underscore the significance of exercising caution when interpreting its findings concerning challenges within LGBT healthcare.

A conceptual framework for landscape-based environmental risk assessment (ERA) of pesticides

While pesticide use is subject to strict regulatory oversight worldwide, it remains a main concern for environmental protection, including biodiversity conservation. This is partly due to the current regulatory approach that relies on separate assessments for each single pesticide, crop use, and non-target organism group at local scales. Such assessments tend to overlook the combined effects of overall pesticide usage at larger spatial scales. Integrative landscape-based approaches are emerging, enabling the consideration of agricultural management, the environmental characteristics, and the combined effects of pesticides applied in a same or in different crops within an area. These developments offer the opportunity to deliver informative risk predictions relevant for different decision contexts including their connection to larger spatial scales and to combine environmental risks of pesticides, with those from other environmental stressors. We discuss the needs, challenges, opportunities and available tools for implementing landscape-based approaches for prospective and retrospective pesticide Environmental Risk Assessments (ERA). A set of “building blocks” that emerged from the discussions have been integrated into a conceptual framework. The framework includes elements to facilitate its implementation, in particular: flexibility to address the needs of relevant users and stakeholders; means to address the inherent complexity of environmental systems; connections to make use of and integrate data derived from monitoring programs; and options for validation and approaches to facilitate future use in a regulatory context. The conceptual model can be applied to existing ERA methodologies, facilitating its comparability, and highlighting interoperability drivers at landscape level. The benefits of landscape-based pesticide ERA extend beyond regulation. Linking and validating risk predictions with relevant environmental impacts under a solid science-based approach will support the setting of protection goals and the formulation of sustainable agricultural strategies. Moreover, landscape ERA offers a communication tool on realistic pesticide impacts in a multistressors environment for stakeholders and citizens.

Corporate Governance Reforms and the Quality of Financial Information of Listed Non-Financial Services Firms in Nigeria

The increasing demand for high quality financial information by the relevant users of financial report has become a serious concern and inevitable on the management of listed non-financial services firms in Nigeria. The primary objective of this study is to examine the nexus between corporate governance reforms and the quality financial information of listed non-financial services firms in Nigeria. Using an ex-post facto as the research design for the study, data was obtained from the secondary sources through the extraction method from the annual financial reports and accounts of the listed firms for 276 firm-year observations, from 2018 to 2023 period. Out of the seventy-five (75) listed non-financial services firms in Nigerian Exchange Group as at 31st December, 2018, a sample size of fourty-six (46) listed firms were used with aid of purposive filter sampling technique. The Feasible Generalized Least Square (FGLS) regression was used as the model estimation technique for the study. Based on the regression analysis, it was found that board size, assurance services and transparency have positive significant impact on financial information quality of listed non-financial services firms in Nigeria. However, sustainability was statistically found to have insignificant impact on quality of financial information of listed non-financial services firms in Nigeria. Therefore, it is recommended that the board of directors of listed non-financial services firms in Nigeria ensure that more members are nominated to participate in the board’s decision. This is because of the fact that larger board sizes are more likely to create avenue for cross-fertilization of ideas thereby, making decisions that can safeguard, uphold and enhance the quality of the financial information of the listed non-financial services firms in Nigeria. The results also underscore the relevance of corporate governance codes and their impacts on FIQ and transparent disclosure. This study offers policy implications to regulatory agencies and standard-setters in their oversight function over the quality of financial information disclosed in annual reports.

Evaluating Artificial Intelligence in Clinical Settings-Let Us Not Reinvent the Wheel.

Given the requirement to minimize the risks and maximize the benefits of technology applications in health care provision, there is an urgent need to incorporate theory-informed health IT (HIT) evaluation frameworks into existing and emerging guidelines for the evaluation of artificial intelligence (AI). Such frameworks can help developers, implementers, and strategic decision makers to build on experience and the existing empirical evidence base. We provide a pragmatic conceptual overview of selected concrete examples of how existing theory-informed HIT evaluation frameworks may be used to inform the safe development and implementation of AI in health care settings. The list is not exhaustive and is intended to illustrate applications in line with various stakeholder requirements. Existing HIT evaluation frameworks can help to inform AI-based development and implementation by supporting developers and strategic decision makers in considering relevant technology, user, and organizational dimensions. This can facilitate the design of technologies, their implementation in user and organizational settings, and the sustainability and scalability of technologies.

Toward More Comprehensive Evaluations of 3D Immersive Sketching, Drawing, and Painting.

To understand current practice and explore the potential for more comprehensive evaluations of 3D immersive sketching, drawing, and painting, we present a survey of evaluation methodologies used in existing 3D sketching research, a breakdown and discussion of important phases (sub-tasks) in the 3D sketching process, and a framework that suggests how these factors can inform evaluation strategies in future 3D sketching research. Existing evaluations identified in the survey are organized and discussed within three high-level categories: 1) evaluating the 3D sketching activity, 2) evaluating 3D sketching tools, and 3) evaluating 3D sketching artifacts. The new framework suggests targeting evaluations to one or more of these categories and identifying relevant user populations. In addition, building upon the discussion of the different phases of the 3D sketching process, the framework suggests to evaluate relevant sketching tasks, which may range from low-level perception and hand movements to high-level conceptual design. Finally, we discuss limitations and challenges that arise when evaluating 3D sketching, including a lack of standardization of evaluation methods and multiple, potentially conflicting, ways to evaluate the same task and user interface usability; we also identify opportunities for more holistic evaluations. We hope the results can contribute to accelerating research in this domain and, ultimately, broad adoption of immersive sketching systems.

Enhancing privacy policy comprehension through Privacify: A user-centric approach using advanced language models

As the digital age advances, the collection, usage, and dissemination of personal data have become critical concerns for users, regulators, and the cybersecurity community. Questions surrounding the extent of identifiable data collection, its usage, sharing, selling, and the mechanisms of consent are increasingly central to discussions on user data privacy. These issues highlight the need for effective management and comprehension of privacy policies. To this end, this paper introduces Privacify— a production-ready web application designed to enhance the accessibility and understandability of privacy policies, thus empowering users to make more informed decisions about their data. At its backend, Privacify leverages a combination of text segmentation, summarization using Large Language Model (LLM), and map-reduce technologies to facilitate BASE analysis for single-document insights and WRT and REV for comprehensive cross-document analysis. Designed with a user-centric approach, Privacify features an intuitive interface that presents all relevant user privacy information in easy-to-understand language, complete with a detailed explainability component. This design not only simplifies privacy policies but also aids users in effortlessly navigating complex privacy terms, significantly boosting their ability to protect and manage their personal information. Our evaluation employs robust methodologies, including reliability and accuracy assessments, alongside rigorous functionality verification through ROUGE metrics and human analysis, validating the system’s efficacy and performance. Privacify’s architecture promotes scalability, replicability, and seamless deployment, advancing the domain of user data protection through improved privacy comprehension.

The problem of protecting the right of a user of internet platforms to an account

The author raises the issue of the formation in the practice of the national regulator of the protection of the rights of users of Internet platforms in terms of illegal blocking and censorship restrictions, contrary to the fundamental principles and guarantees of freedom of collection, receiving and disseminating information and the right to freedom of expression in a democratic society. The author, analyzing the decision of the Federal Antimonopoly Service and other normative acts, states that the relevant judicial and administrative practice has not been generalized and logically developed in the form of amendments and additions to legislative acts. At the same time, the author concludes that the relevant user rights continue to be massively violated despite the imposition of large fines by both Russian courts and other State authorities. In the author’s view there is insufficient protection of user’s rights and redress.

“The story just brings the science to life”: exploring the use of stories to translate knowledge about self-regulatory processes during goal striving in running

ABSTRACT Storied representations of research have been recommended and identified as an effective pedagogical tool to facilitate knowledge transfer to end users. However, storied forms of representation have not yet been used to communicate knowledge of self-regulation during goal striving in running. Therefore, building upon a previous programme of research represented via a traditional realist tale (Jackman et al., 2024), the study aims were twofold: (1) to construct stories that communicate runners’ lived experiences of self-regulation during goal striving in distance-running; and (2) to share these stories with relevant knowledge users to explore what they do on and for them in the short-term (1–2 weeks) and long-term (six months). Stories were constructed and represented through vignettes. To accommodate diverse views and appreciate different knowledge bases, we invited athletes, coaches, and sport psychologists to witness the vignettes and explored their responses via qualitative surveys and multiple interviews over time. Data analysis identified how the stories were useful for translating knowledge into practice, the reasons why, and how they acted on and for the participants. The accessibility of the stories enabled participants to connect meaningfully with the research. This expanded their knowledge, which some used in performances and to support other runners. Overall, our findings support an evolving body of research illustrating the potential of storied forms of representation to facilitate knowledge transfer, and extend understanding by providing a subject-specific (i.e., self-regulation and goal striving) and population-specific (i.e., running) example of how stories can work on and for athletes and practitioners.

Core socioDemographic data variables in ICU Trials (CoDe-IT): a protocol for generating core data variables using a Delphi consensus process

IntroductionSociodemographic variables influence health outcomes, either directly (ie, gender identity) or indirectly (eg, structural/systemic racism based on ethnoracial group). Identification of how sociodemographic variables can impact the health of critically...

A novel, noninvasive, multimodal screening test for the early detection of precancerous lesions and colorectal cancers using an artificial intelligence–based algorithm.

3627 Background: Colorectal cancer (CRC) ranks as the second leading cause of cancer-related mortality worldwide, and its incidence is increasing in younger populations. Detection of early-stage CRC and its precursor lesions, such as advanced adenomas (AA), is crucial for successful treatment and reduces CRC-related mortality. Although non-invasive methods for early detection are available and increase screening compliance, their performance with respect to detection of advanced adenomas and early-stage cancers is limited. Here, we describe a novel and non-invasive stool-based approach combining diagnostic biomarkers with an algorithm generated by machine learning/artificial intelligence (ML/AI) resulting in significantly improved diagnostic performance for the detection of not only CRC, but especially precancerous lesions like AA. Methods: Data were generated from a combined cohort of stool samples collected at 10 clinical sites in Europe (COLOFUTURE study) and 21 clinical sites in the US (eAArly DETECT study). The evaluable study cohort consists of 690 subjects, including 78 CRC, 146 AA, 147 with non-advanced adenoma (AD) and 319 normal colonoscopy negative control (NC) subjects (49% female, 51% male, average age 61.8 years). Results were compared with colonoscopy and pathology findings to determine sensitivity and specificity for detection of early-stage CRC and AA vs. AD and NC. Nucleic acids were extracted from stabilized stool samples using a silica bead-based extraction method. Expression of mRNA biomarkers was analyzed utilizing Real-Time PCR. Human hemoglobin was quantified using FIT. The Emerge Quantitative Evolution ML/AI platform was leveraged to develop classifiers capable of distinguishing CRC and AA from AD and NC. Results: Applying the combined approach of non-invasive diagnostic testing with an AI/ML generated algorithm, the sensitivity for detection of CRC overall was 92.3%. In addition, this method enabled AA detection with a sensitivity of 82.2%. Specificity turned out to be 90.1 % (AD+NC). Conclusions: This innovative, non-invasive, multimodal screening strategy based on self-collected stool samples which combines mRNA expression patterns and FIT analysis with an AI/ML-generated algorithm represents a substantial improvement in the effectiveness of non-invasive CRC screening. Such improvements in usability and performance leading to reliable detection of early-stage CRC and precursor lesions, such as advanced adenomas, are required for wide-spread availability and adaption of non-invasive screening tests to accepted clinically relevant usage and to prevent the development of CRC effectively.

Performance evaluation of off-grid solar systems for critical medical instruments in remote regions

In areas with limited access to electricity or during power outages, ensuring continuous and reliable use of grid-powered electrical instruments is challenging, especially in remote emergency centers. A stable source of electricity is crucial to prevent disruptions in power supply, as they can lead to severe medical complications, jeopardize patient well-being, and even result in fatal incidents. To address this issue, integrating renewable electricity sources such as off-grid solar systems into existing power supply infrastructure can be a viable solution. Recent studies suggest that off-grid solar systems can be reliable and sustainable options for powering medical facilities, particularly in areas lacking uninterrupted grid connectivity. Therefore, this research aims to evaluate the feasibility, benefits, and challenges of integrating off-grid power to support critical medical instruments. Based on an extensive literature review, interviews with experts, and surveys among relevant users, this study finds that the system has the capability to maintain a consistent, dependable power supply, even during adverse weather conditions. Cost and feasibility are highlighted as paramount considerations, based on surveys and focus group results. The study concludes that off-grid solar systems offer an economical, low-maintenance, and environmentally sustainable alternative for remote medical facilities. Finally, this study proposes recommendations to optimize critical device performance during power outages and improve overall system functionality and efficiency.

Patient, caregiver and other knowledge user engagement in consensus-building healthcare initiatives: a scoping review protocol

IntroductionPatient engagement and integrated knowledge translation (iKT) processes improve health outcomes and care experiences through meaningful partnerships in consensus-building initiatives and research. Consensus-building is essential for engaging a diverse group...

Development of a pharmaceutical database as an aid to the nonclinical detection of drug-induced cardiac toxicity

The Health and Environmental Sciences Institute (HESI) Cardiac Safety Committee designed and created a publicly accessible database with an initial set of 128 pharmacologically defined pharmaceutical agents, many with known cardiotoxic properties. The database includes specific information about each compound that could be useful in evaluating hypotheses around mechanisms of drug-induced cardiac toxicity or for development of novel cardiovascular safety assays. Data on each of the compounds was obtained from published literature and online sources (e.g., DrugBank.ca and International Union of Basic and Clinical Pharmacology (IUPHAR) / British Pharmacological Society (BPS) Guide to PHARMACOLOGY) and was curated by 10 subject matter experts. The database includes information such as compound name, pharmacological mode of action, characterized cardiac mode of action, type of cardiac toxicity, known clinical cardiac toxicity profile, animal models used to evaluate the cardiotoxicity profile, routes of administration, and toxicokinetic parameters (i.e., Cmax). Data from both nonclinical and clinical studies are included for each compound. The user-friendly web interface allows for multiple approaches to search the database and is also intended to provide a means for the submission of new data/compounds from relevant users. This will ensure that the database is constantly updated and remains current. Such a data repository will not only aid the HESI working groups in defining drugs for use in any future studies, but safety scientists can also use the database as a vehicle of support for broader cardiovascular safety studies or exploring mechanisms of toxicity associated with certain pharmacological modes of action.

E-commerce and consumer behavior: A review of AI-powered personalization and market trends

In the dynamic landscape of electronic commerce (e-commerce), understanding and adapting to evolving consumer behavior is critical for the sustained success of online businesses. This review delves into the intersection of e-commerce and consumer behavior, focusing on the transformative role of Artificial Intelligence (AI)-powered personalization and its impact on market trends. The advent of AI has revolutionized the way e-commerce platforms engage with and cater to individual consumer preferences. AI-powered personalization techniques leverage advanced algorithms to analyze vast datasets, enabling the delivery of highly tailored and relevant content, product recommendations, and user experiences. This review explores the intricate mechanisms of AI-driven personalization, examining how it enhances customer engagement, satisfaction, and loyalty. Furthermore, the study investigates the prominent market trends shaped by AI in e-commerce. From chatbots and virtual assistants facilitating seamless customer interactions to predictive analytics optimizing inventory management, AI is driving innovation across various facets of the online retail landscape. The analysis delves into the integration of machine learning algorithms in predicting consumer preferences, streamlining the purchasing process, and fostering a more personalized shopping journey. As e-commerce continues to evolve, the review also explores the challenges and ethical considerations associated with AI-powered personalization. Issues such as data privacy, algorithmic bias, and the delicate balance between customization and intrusiveness are examined to provide a comprehensive understanding of the broader implications of AI in shaping consumer behavior. Ultimately, this review offers valuable insights into the symbiotic relationship between e-commerce and consumer behavior, shedding light on the transformative power of AI-powered personalization and its influence on emerging market trends. As businesses navigate the digital landscape, understanding and harnessing the potential of AI-driven strategies become imperative for staying competitive and meeting the evolving expectations of tech-savvy consumers.

The Influence of Chinese Online Novels on the Values of Adolescents

Introduction. With the development of the Internet, the popularity of online novels, especially in China, prompts the declining interest in reading paper books. The potential impact of online novels on adolescents has become a matter of public concern. Most studies examine the role of online novels in students’ learning process, as well as the impact on young people’s communication and social interaction. However, so far, the impact of online novels on adolescents’ values and psychology has been understudied despite their critical importance in shaping young peopleʼs identity. Therefore, the purpose of this study is to determine the influence of online novels on the values and psychology of Chinese secondary school learners. Materials and Methods. To address this challenge, a survey was conducted among students attending Yifu Educational Institution in Nanning, China. Questionnaires developed through the Question Star app were distributed through relevant user groups on social media platforms including WeChat and Tencent QQ. Results. As a result, positive (increased general knowledge and literacy, the opportunity to spend free time productively) and negative (impact on learning and physical health, decreased literary abilities, promotion of tendencies harmful for society) characteristics of the influence of online novels on adolescents were identified. Practical recommendations were formulated aimed at counteracting negative impact of online novels on adolescents such as the need to strengthen the ideological and moral education of students, the necessity to develop national cultural superiority and pride of modern youth, as well as to introduce young people to useful bibliography. Discussion and Conclusion. The results obtained will make a significant contribution to such fields as psychology, sociology and education. Also, the results of the study will serve as a basis for the development of new approaches to combat the negative impact of Internet novels on the values of adolescents. The results of the study may be useful for specialists of educational institutions and all those who care about the upbringing of the younger generation.

Privacy Protection Based on Federated Learning

With the development of artificial intelligence technology, more and more fields will collect relevant user data, and provide users with a better experience through data analysis. But there are also risks involved in the process of data collection, namely how to protect personal privacy data. To address this issue, this study combined differential privacy, convolutional neural networks, and federated averaging algorithms to construct a privacy protection model. The study first utilized the federated average algorithm to handle data imbalance, ensuring that each analyzed data is in a balanced state. Then, based on of data balancing, a new algorithm model was constructed using differential privacy and convolutional neural networks. Finally, it utilized a number of public datasets to verify the role of the model in privacy protection. The results showed that the model can achieve recognition accuracy of 97.27% and 93.15%, respectively , for data under the influence of privacy budget and relaxation factor. Meanwhile, the classification accuracy of the model for data can reached 95.31%, with a regression error of 9.03%. When the local iteration number of the device was 30, the testing accuracy can reached 95.28%. This indicates that methods on the grounds of federated averaging algorithm and differential privacy can maintain the accuracy of the model while protecting user privacy. The application research of models has strong practical significance.

Generating user-driven patient personas to support preventive health care activities of rural-living unattached patients

ObjectiveThis study created personas using quantitative segmentation and knowledge user enhancement to inform intervention and service design for rural patients to encourage preventive care uptake. MethodsThis study comprised a cross-sectional survey of rural unattached patients and a co-design workshop for persona development. Cross-sectional survey data were analyzed for meaningful subgroups based on quartiles of preventive care completion. These quartiles informed “relevant user segments” grouped according to demographics (age, sex), length of unattachment, percentage of up-to-date preventive activities, health care visit frequency, preventive priorities, communication confidence with providers, and chronic health conditions, which were then used in the workshop to build the final personas. Results207 responses informed persona user segments, and five health care providers and 13 patients attended the workshop. The resulting four personas, included John (not up-to-date on preventive care activities), Terrance (few up-to-date preventive care activities), George (moderately up-to-date preventive care activities), and Anne (mostly up-to-date preventive care activities). ConclusionQuantitative persona development with integrated knowledge user co-design/enhancement elevated and enriched final personas that achieved robust profiles for intervention design. InnovationThis project's use of a progressive methodology to build robust personas coupled with participant feedback on the co-design process offers a replicable approach for health researchers.