Ethical Issues in Data Collection: A Commentary

The incorporation of artificial intelligence (AI) into gastrointestinal (GI) endoscopy represents a promising advancement in gastroenterology. With over 40 published randomized controlled trials and numerous ongoing clinical trials, gastroenterology leads other medical disciplines in AI research. Computer-aided detection algorithms for identifying colorectal polyps have achieved regulatory approval and are in routine clinical use, while other AI applications for GI endoscopy are in advanced development stages. Near-term opportunities include the potential for computer-aided diagnosis to replace conventional histopathology for diagnosing small colon polyps and increased AI automation in capsule endoscopy. Despite significant development in research settings, the generalizability and robustness of AI models in real clinical practice remain inconsistent. The GI field lags behind other medical disciplines in the breadth of novel AI algorithms, with only 13 out of 882 Food and Drug Administration (FDA)-approved AI models focussed on GI endoscopy as of June 2024. Additionally, existing GI endoscopy image databases are disproportionately focussed on colon polyps, lacking representation of the diversity of other endoscopic findings. High-quality datasets, encompassing a wide range of patient demographics, endoscopic equipment types, and disease states, are crucial for developing effective AI models for GI endoscopy. This article reviews the current state of GI endoscopy datasets, barriers to progress, including dataset size, data diversity, annotation quality, and ethical issues in data collection and usage, and future needs for advancing AI in GI endoscopy.

The Covid-19 pandemic strongly impacted most areas of human life, including research. Many of the studies in this period had to adapt to the limitations caused by the regulations and restrictions imposed as a result of the pandemic. Qualitative research occupies a relevant position in the field of educational research. The common feature of this type of research is the close relationship between researchers and participants. This element was called into question, with digital tools having emerged as a promising solution for data collection. An intensification of the use of digital tools for data collection in qualitative research calls for a careful analysis and reflection concerning their strengths and weaknesses. The aim of this article is to analyse the methodological aspects of qualitative data collection through a systematic literature review, focusing on the use of digital tools in the context of educational studies during the pandemic. The main results highlight the increased significance of technology-mediated data collection in educational research post-Covid-19, with the USA leading in publications. Predominantly, current studies focus on teachers’ perceptions and practices, underscoring the multifaceted nature of teaching. Interviews, often conducted via video calls or videoconferencing, were the most common data collection method. The transition from face-to-face to technology-mediated data collection in these studies shows the limited discussion of implications or ethical issues. This article provides insights into the use of technology-mediated tools, contributing to the advancement of methodological knowledge in times of crisis when the traditional use of qualitative data collection methods is compromised.

The Internet offers a “virtual world” in which to carry out innovative sex research, but this new world may entail new ethical dilemmas. Ethical issues in recruitment, informed consent, data collection, and record keeping are examined. Applying common sense and current ethical codes for conducting sex research are sufficient in most cases. Special care and procedures may be required to obtain data from children and to protect the privacy of sensitive data and records. Researchers should be aware of, and should report, threats to data integrity and potential biases in participants' responses when they respond by computer.

This paper provides an overview of current ethical concerns in image-based research. It considers the influence of institutional structures such as regulatory frameworks, professional guidelines and institutional review boards before focusing on issues of data collection and dissemination. The paper discusses informed consent, anonymity and confidentiality, specifically in relation to how they may differ in image-based compared to word-based research. It is suggested that a situated approach to image-based ethics is better able to take account of the concrete, everyday situations within which ethics are negotiated between researchers and research participants.

Rare disease patient registries are indispensable tools for translating research into improved care and therapeutic solutions. During the race to identify a safe and effective treatment, they come into play at many stages of the translational research cycle: collection of mutational data, description of the disease, support for patient recruitment for clinical trials and scientific studies (such as natural history studies), collection of epidemiological data, evaluation/monitoring of the efficacy/safety of a treatment, elaboration of guidelines for diagnosis and management of the disease, etc. In the field of rare disease, the main challenges that patient registries face are sustainability, better interoperability with the establishment of common data standards (for data collection, data quality, data security, legal and ethical issues) and support for translational collaborations to constitute large cohorts of patients. To work out these questions, the IRDiRC (International Rare Disease Research Consortium) initiative is a major force to encourage cooperation at international level. In this process, patients and families are becoming more active participants and must continue to raise their voice to drive innovation in collaboration with all stakeholders.

Methods in Intercultural Pragmatics are inherently multifaceted and varied, given discipline’s breaching of numerous cross-disciplinary boundaries. In fact, research in Intercultural Pragmatics represents merely new ways of thinking about language and, thus, of researching interactants’ (non-)verbal behaviors: With core common ground and shared knowledge about conventionalized frames of the target language being limited, intercultural communication features a number of unique characteristics in comparison to L1 communication. This being said, the range of methods employed in data collection and analysis in Intercultural Pragmatics is not only wide, but highly heterogeneous at the same time. The present paper takes a scientometric approach to data collection methods and data types in Intercultural Pragmatics research. In order to provide an extensive diachronic survey of methods and approaches featuring in empirical studies published specifically by the journalIntercultural Pragmatics(edited by Istvan Kecskés), this study includes a self-compiled corpus of 358 papers in 17 volumes published since its launch in 2004 thru 2020. The aim is to carve out diachronic method preferences and emerging as well as declining trends in data collection methods and data types adhered to within this discipline. These are further discussed within the context of relevant state-of-the-art accounts that have specifically offered surveys of methods and methodologies pertaining to issues in data collection and data analysis in (Intercultural) Pragmatics in recent years.

Data management in maintenance outsourcing

Foreword N. Sadik. 1. The State of the Art and Overview of the Chapters R.E. Bilsborrow. Part 1: Old and New Patterns of Internal Migration and Urbanization in Developing Countries. 2. What Do We Know About Recent Trends in Urbanization? N. Chen, et al. 3. Recent Internal Migration Processes in Sub-Saharan Africa: Determinants, Consequences, and Data Adequacy Issues J.O. Oucho. 4. New Trends in Urban Settlement and the Role of Intraurban Migration: The Case of Sao Paulo/Brazil J.M. Pinto da Cunha. Part 2: Migration Determinants and Linkages with Economic Growth. 5. Rural Out- Migration in China: A Multilevel Model Junming Zhu. 6. Migration Motivation, Family Links, and Job Search Methods of Rural-to-Urban Migrants in India B. Banerjee. 7. Measuring the Macroeconomic Impact of Internal Migration: A Production Function Approach with Evidence from Peru A. Morrison, Xin Guo. Part 3: The Consequences of Migration. 8. Migration and Urbanization in West Africa: Methodological Issues in Data Collection and Inference P. Bocquier, S. Traore. 9. Assessing the Consequences of Internal Migration: Methodological Issues and a Case Study on Thailand Based on Longitudinal Household Survey Data P. Guest. 10. Rural-Urban Migration and Development: Evidence from Bangladesh R. Afsar. 11. Migration and the Fertility Transition in African Cities M. Brockerhoff. Part 4: Migration, Urbanization Processes, and Implications. 12. A Reassessment of Migration and Urbanization in Mexico in the 20thCentury C.B. Paz. 13. The Coping Capacity of Latin America's Cities A.G. Gilbert. 14. Urban Economic Growth in the 21st Century: Assessing the International Competitiveness of Metropolitan Areas D.A. Rondinelli, G. Vastag. Appendix: Internal Migration and Urbanization Recommendations. Symposium on Internal Migration and Urbanization in Developing Countries: Implications for Habitat II.

BackgroundIn 2019–20, approximately 52,300 Australians were admitted to hospital for sports injuries but there is limited national data to quantify injuries not requiring a hospital admission.AimsTo investigate sports injury data...

The analysis of vulnerability processes throughout life implies several methodological difficulties. In this review chapter, we look back on more than 10 years of methodological innovations developed within the NCCR LIVES. Concerning data collection issues, although the prospective survey remains the gold standard for obtaining longitudinal data, retrospective data collected through specially adapted tools such as life calendars allow for a rapid completion of data sequences. Moreover, alternative sampling schemes based on network methods can reach individuals not likely to be included in traditional probabilistic samples. This also requires the development and use of more global data collection modes, combining qualitative and quantitative data, and allowing participants to respond in the manner best suited to their specific situations and capacities. What is true regarding data collection is also a requirement for data analysis: it is often essential to combine the strengths of different analytical tools such as traditional longitudinal analyses and survival analysis, the aim being to study the occurrence of specific events without losing sight of an individual’s prior trajectories over their life course. Finally, the chapter also addresses the issues of multichannel analyses and missing data.

This chapter discusses the execution of the research on the coexistence of private label and manufacturer brands in food product categories in a grocery retail landscape characterised by high retail consolidation and concentration. The main focus of this chapter is data collection and data analysis procedures. Data collection issues are discussed first, and these include techniques of data collection, secondary data, in-store category observation study, in-depth interviews and a pilot study; followed by a discussion of data analysis procedures. Ethical considerations are also addressed.

Despite the growing popularity of learning analytics in higher education, its development status in Asia was barely studied. This paper reports a study on the development of learning analytics in higher education in Asia. Semi-structured interviews were conducted with eight senior managers or senior academics from various tertiary institutions in Asia. The participants were asked about their institutions’ position on learning analytics, the progress in its implementation, factors leading to effective implementation, and challenges encountered, if any. The results showed that in those institutions where learning analytics has been implemented, it aimed mainly at enhancing student retention, pedagogy and student learning experience. Its effective implementation relies on support from senior management, and taking students’ views into account in decision-making. The participants’ institutions encountered difficulties due to teachers’ and students’ concerns, such as the increased workload and data privacy, as well as technical issues in data collection, processing and analysis. In short, though starting late in Asia, learning analytics has been gradually gaining attention and is being implemented. The future directions of research and practices in learning analytics are also discussed.

Neurotoxicity of organic solvents is one of the most important emerging issues in the field of occupational health. Psychological testing has been proven useful not only in clinical diagnosis but also in experimental and epidemiological studies. Although various psychobehavioral performance test batteries have been applied in the study of neurotoxicity of organic solvents during these last two decades among European countries and America, only few studies have been made on these in Japan. It is therefore considered very important to review the major papers published to date, clarify the issues being currently discussed, and propose important studies for future. The present paper provides a review of the results obtained by the application of behavioral performance tests in the study of solvent toxicity. The studies reviewed are classified into the following five parts: 1. psychological test batteries developed to date, 2. human experimental studies and experimental field studies on the acute toxicity of organic solvents, 3. epidemiological studies on industrial workers, 4. characteristics of the central nervous system dysfunction caused by organic solvents, and 5. prognosis of workers diagnosed as chronic organic solvent intoxication. The paper also discusses the applicability of psychobehavioral techniques and addresses issues in data collection in the study of the effects of solvent exposure on the nervous system.

Species mapping methods play a central role in biogeographical questions, as they may generate a domino effect on further works based on species distribution. In light of the massive recent increase in the availability of online occurrence data, we highlight the strengths and limitations of the mapping methods most widely used to display the geographic distribution of plants, namely geographic range maps and occurrence record maps. We use the modern distribution of the genus Arbutus in western Eurasia, North Africa, and Macaronesia, for which no occurrence record map has been published yet, to discuss critical issues in data collection and representation. The occurrence record map of A. unedo, A. andrachne, A. canariensis, and A. pavarii shows how well this mapping method captures the details of peripheral and isolated stands as well as the variability of population density. A number of biogeographical issues are addressed by this approach, including the determination of the chorological centre of gravity in relation to historical dynamics, genetic patterns in relation to range porosity, and the autochthony status of marginal stands. These issues constitute the necessary foundation for additional palaeobotanical research and ecological modelling to investigate the past-to-future dynamics of Arbutus and other species of the Mediterranean–Atlantic area.

This book studies user privacy issues in data collection and data processing, which mainly involves the privacy-preserving content-based task allocation, the privacy-preserving location-based task allocation, the privacy-preserving truth discovery with truth transparency, and the privacy-preserving truth discovery with truth hiding. To realize the above schemes, the basic knowledge used in this chapter includes polynomial function, secure hash function, searchable encryption, asymmetric scalar-product-preserving encryption, polynomial fitting, truth discovery, and public-key cryptosystem supporting distributed decryption. The relevant basic knowledge is introduced as follows.