Data Collection Practices Research Articles

Examining the Landscape of Prognostic Factors and Clinical Outcomes for Cancer Control

Prognostic factors have important utility in various aspects of cancer surveillance, including research, patient care, and cancer control programmes. Nevertheless, there is heterogeneity in the collection of prognostic factors and outcomes data globally. This study aimed to investigate perspectives on the utility and application of prognostic factors and clinical outcomes in cancer control programmes. A qualitative phenomenology approach using expert interviews was taken to derive a rich description of the current state and future outlook of cancer prognostic factors and clinical outcomes. Individuals with expertise in this work and from various regions and institutions were invited to take part in one-on-one semi-structured interviews. Four areas related to infrastructure and funding challenges were identified by participants, including (1) data collection and access; (2) variability in data reporting, coding, and definitions; (3) limited coordination among databases; and (4) conceptualization and prioritization of meaningful prognostic factors and outcomes. Two areas were identified regarding important future priorities for cancer control: (1) global investment and intention in cancer surveillance and (2) data governance and exchange globally. Participants emphasized the need for better global collection of prognostic factors and clinical outcomes data and support for standardized data collection and data exchange practices by cancer registries.

ECtHR jurisprudence on the matter collection of personal data

The protection and storage of personal data are clearly related to the right to respect for privacy, as guaranteed by art. 8 of the European Convention on Human Rights. The latter provision protects a whole range of rights, namely the right to respect for private and family life, home and correspondence. The principle is that art. 8 protects personal information in respect of which an individual can legitimately hope that it will not be published or used without his or her consent. The study aims to break into the jurisprudence of the European Court of Human Rights, the main objective being to identify decisions that have a fundamental impact on the doctrine and practice of personal data collection. We are aware that multiple regulations in the field of personal data collection can be deduced from the practice of the Court of Justice of the European Union (CJEU). However, given the direct impact of ECtHR decisions on the Republic of Moldova, we found it appropriate to summarize only this aspect. However, in subsequent studies we will address the issue of personal data protection by the Court of Justice of the European Union. The basic idea, derived from that study, is that the Moldovan authorities should adjust their legislation and practices to the standards set out by the ECtHR and thus avoid possible convictions by the European Court.

The commercialisation of school administration: one school’s enactment of a student management system in Aotearoa New Zealand

ABSTRACT The intensification of data collection practices in schooling – often due to state accountability requirements – has resulted in the widespread adoption of commercial student management systems (SMS) in schools. Drawing on a qualitative case study of a New Zealand primary school, this paper investigates its adoption of a commercial SMS, and the ways this product re-engineers schooling processes, including what student data is collected, how school decisions are made, and when work is done by staff. Through this analysis, we argue direct-to-school commercial relationships constitute a new configuration of public–private partnerships in education. We demonstrate the rise of a local education market for data management where responsibility is placed on individual schools to choose a commercial product that will interface with the needs of a public bureaucracy. We end this paper with a critical discussion about how the commercialisation of school administration affects the broader infrastructures of public schooling.

Blockchain Technology in Wine Chain for Collecting and Addressing Sustainable Performance: An Exploratory Study

Sustainability standards have not yet been commonly adopted by the whole wine chain, and indicator assessments are not widely spread. A deep understanding of how embedding sustainability into business while controlling costs related to the adoption of sustainability certification standards such as data collection and management practices could allow one to overcome most barriers relevant to sustainability compliance. Blockchain technology (BCT) may answer these needs. In order to verify BCT potential to be used as a sustainability management tool in the wine industry, with a qualitative triple bottom line research approach, this article explores the connections among BCT adoption in agri-food, issues posed by wine sustainability certification, and whether wine companies that already own a wine sustainability certification are prepared to adopt it. Results show that (1) the blockchain allows collecting data and information that are relevant for monitoring and improving sustainability: Soil and water features, climate conditions, treatment with pesticides and fertilizers, production process, traceability, transparency, labor and human rights, quality and safety, waste reduction, authenticity, relationship with stakeholders; (2) wine companies that already own a sustainability certification have little familiarity with blockchain applications (57.1%, n.21) and only 14% of the respondents support their intention to invest in BCT in the coming years; (3) the case study shows improvements in traceability and transparency along the supply chain and an increase in consumers’ trust that was reflected in sales growth, and the main costs are linked to complexity in data management.

Re-imagining the space age: Early satellite development from Earthly fieldwork practice

ABSTRACT Imagining space technology has been influenced by (usually American-centred) turning points in rocketry, launchers, space exploration and human spaceflight: principally in terms of techno-bureaucratic Big Science products embedded in Cold War rivalry, military and prestige objectives. While this representation is useful to understand many developments of the space age, it has tended to downplay the role of natural history practices of data collection and interpretation in the development of space technology. The notion of sociotechnical imaginary helps to reveal a more complex and complete understanding of the history of space technology. Between 1967 and 1973, the vision of the French remote-sensing satellite as both enabled by and an extension of aircraft photo-interpretation helped to shape scientific and technological expectations of remote-sensing technology. In turn, the practices, values, and visions of aircraft photo-interpreters informed the development of satellite remote-sensing work. In particular, the fieldwork-driven research mode, focusing on data collection and field observations, was an important part of satellite technology development –a tie which remains strong today. Approaching remote-sensing satellite technology through historical research not only suggests a particular way of imagining space technology within the tradition of field science practices, discourses, and history, but also allows us to reflect on the power and limitations of prevalent imaginaries to fully understand the space age and its place in history.

Data Quality Assurance Begins Before Data Collection and Never Ends: What Marketing Researchers Absolutely Need to Remember

Data quality has become an area of increasing concern in marketing research. Methods of collecting data, types of data analyzed, and data analytics techniques have changed substantially in recent years. It is important, therefore, to examine the current state of marketing research, and particularly self-administered questionnaires. This paper provides researchers important advice and rules of thumb for crafting high quality research in light of the contemporary changes occuring in modern marketing data collection practices. This is accomplished by a proposed six-step research design process that ensures data quality, and ultimately research integrity, are established and maintained throughout the research process—from the earliest conceptualization and design phases, through data collection, and ultimately the reporting of results. This paper provides a framework, which if followed, will result in reduced headaches for researchers and more robust results for decision makers.

Law enforcement suicide: The depth of the problem and best practices for suicide prevention strategies

The purpose of this research study was to review the current literature on the prevalence of suicide deaths, attempts, and ideation, and resistance for seeking help among law enforcement officers by examining current suicide prevention programs among those that support the country's police officers. The exact number of law enforcement officer deaths by suicide is unknown due to inconsistent data collection practices. Approximate estimates range from being at or significantly above the national average; one study reported the rate of suicide to be twice the rate of officers who die in the line of duty, another study reported three times the rate and another reported to be eight times that of the general population. The inconclusive nature of the literature has made obtaining the number of officer suicide deaths challenging. A comprehensive examination of the law enforcement mental health and suicide prevention literature revealed a lack of consistency in reporting; a multitude of maladaptive behaviors; and a lack of adequate suicide prevention programing for this profession. • Law enforcement officer rates of suicide are higher than the general population. • Relationship problems and job stress are the top variables among officer suicides. • Critical events contribute to officers' trauma and stress, increasing suicide risk. • Leadership must instill a department mentality of help-seeking from a top-down response. • Suicide prevention for law enforcement officers requires unique interventions.

"American Indian" as a Racial Category in Public Health: Implications for Communities and Practice.

When public health considers the health and disease status of Indigenous people, it often does so using a racial lens. In recent decades, public health researchers have begun to acknowledge that commonly employed racial categories represent history, power dynamics, embodiment, and legacies of discrimination and racism, rather than innate biology. Even so, public health has not yet fully embraced an understanding of other components of identity formation for Indigenous people, including political status within Native nations. In this article, we discuss why the continued racial conceptualization of Indigeneity in US public health is inadequate. We begin by providing a brief account of racialization as a tool of colonization, of failure to recognize and acknowledge Indigenous sovereignty, and of common public health practices of Indigenous data collection and interpretation. We then articulate the stakes of racialized health data for Native communities. We end by offering alternative approaches, many drawn from scholarship from Indigenous researchers. (Am J Public Health. 2021;111(11):1969-1975. https://doi.org/10.2105/AJPH.2021.306465).

4.B. Workshop: Data collection during COVID-19 pandemic and its policy impacts

The workshop has the aims to review practices for reliable and robust data collection during disaster such as the COVID-19 pandemic and to develop implementation practices. Study conduct is even more necessary in times of crises and at the same time more challenging. We review existing practices by bringing together three aspects of study conduct in times of crises: 1) experiences with sampling methods, 2) experiences with exposure assessment and 3) development of evidence based policy guidelines. First, experiences with different sampling approaches to collect longitudinal data on in a multicentre study during the COVID19 pandemic are presented (Felix Sisenop). Second, exposure assessment methods in different cultural traditions are presented and reflected (Edvaldo Begotaraj). Third, the challenge of rapid evidence based policy development will be reviewed (Marija Jakubauskiene). It will be shown, how data gathered in an international consortium can have impact on a national level through policy advisory. Ensuring the ability to provide robust and reliable data on psychosocial and mental health service responses to crises is an important step for emergency preparedness. The lessons learnt will be discussed with workshop participants.Key messages Rapid study conduct is necessary in times of crises.Methods of rapid study conduct need further development.

The Value and Interpretation of Race and Ethnicity Data in the Era of Global Migration: A Change Is in Order.

ABSTRACT.Human migration and travel are leading to increasingly diverse populations throughout the world. Data collection practices need to adapt to these changes to expand our understanding of health disparities and to optimize the efforts to address health equity, particularly during public health emergencies such as the current COVID-19 pandemic. Race and ethnicity classifications in the United States have failed to evolve since the 1970s despite an increasingly diverse population. Current commonly collected categories are inadequate to accurately describe the economic, educational, and sociopolitical circumstances of different groups. Further, these categories lend little practical information to inform health policy. More predictive and actionable variables should be routinely collected to improve appropriateness and timeliness of health interventions. The immediate adoption of the collection of primary/preferred language and country of birth/origin by public health organizations, health systems, and clinical providers would be a concrete and valuable first step.

Microphone placement investigation for standard aircraft ground run-up noise measurements

The correct placement (height, orientation, and mounting techniques) for microphones used in standard data collection practices for aircraft environmental noise models is a topic of frequent debate. Previous studies have demonstrated and quantified the dependence of spectral data recorded as a function of microphone placement variations and relative source origin. In this work, an in-depth investigation of microphone mounting effects is performed with an emphasis on (1) microphone height and (2) ground-mounting configuration for the purpose of quantifying ground run-up aircraft noise emissions for environmental noise model generation. Data for this investigation were collected on the T-7A Red Hawk in both standard (see ANSI S12.75-2012) and off-standard configurations for comparison.

Developments in Qualitative Mindfulness Practice Research: a Pilot Scoping Review

ObjectivesWhile scholars are increasingly emphasizing the potential of qualitative mindfulness practice research (QMPR) for advancing the understanding of mindfulness practice, there has been no significant empirical inquiry looking at actual trends and practices of QMPR. Consequently, it has been impossible to direct research practices toward under-researched areas and make methodical suggestions on how to approach them. The aim of the present study was to analyze current trends and practices in QMPR in order to address these areas of need.MethodsBased on a scoping review, 229 qualitative studies published between 2000 and 2019 were analyzed in regard to their disciplinary backgrounds, research questions and intentions, type of mindfulness practice, target population, as well as practices of data collection and analysis.ResultsA strong focus of QMPR lies in the inquiry of mindfulness-based interventions, particularly mindfulness-based stress reduction, mindfulness-based cognitive therapy, and adaptations. Over 10% of the publications do not fully specify the mindfulness practice. The efficacy and subjective experience of mindfulness practices constitute the dominant research interests of QMPR. Data collection is highly concentrated on practice participants and first-person data. Interpretative paradigms are the predominant analytical approach within QMPR. QMPR studies have a strong proclivity toward emphasizing the positive effects of mindfulness practice. Nine percent of all articles considered for our study did not fully disclose their analytical procedure. Adversarial research groups and pluralistic qualitative research remain scarce.ConclusionsFuture QMPR should (i) include second- and third-person data, (ii) include dropouts and former mindfulness practitioners, (iii) fully disclose details on the mindfulness practice and data analysis, (iv) intensify the application of critical and deconstructivist paradigms, as well as pluralistic qualitative research, and (v) build adversarial research teams.

Quality of Hospital Electronic Health Record (EHR) Data Based on the International Consortium for Health Outcomes Measurement (ICHOM) in Heart Failure: Pilot Data Quality Assessment Study.

BackgroundThere is increasing recognition that health care providers need to focus attention, and be judged against, the impact they have on the health outcomes experienced by patients. The measurement of health outcomes as a routine part of clinical documentation is probably the only scalable way of collecting outcomes evidence, since secondary data collection is expensive and error-prone. However, there is uncertainty about whether routinely collected clinical data within electronic health record (EHR) systems includes the data most relevant to measuring and comparing outcomes and if those items are collected to a good enough data quality to be relied upon for outcomes assessment, since several studies have pointed out significant issues regarding EHR data availability and quality.ObjectiveIn this paper, we first describe a practical approach to data quality assessment of health outcomes, based on a literature review of existing frameworks for quality assessment of health data and multistakeholder consultation. Adopting this approach, we performed a pilot study on a subset of 21 International Consortium for Health Outcomes Measurement (ICHOM) outcomes data items from patients with congestive heart failure.MethodsAll available registries compatible with the diagnosis of heart failure within an EHR data repository of a general hospital (142,345 visits and 12,503 patients) were extracted and mapped to the ICHOM format. We focused our pilot assessment on 5 commonly used data quality dimensions: completeness, correctness, consistency, uniqueness, and temporal stability.ResultsWe found high scores (>95%) for the consistency, completeness, and uniqueness dimensions. Temporal stability analyses showed some changes over time in the reported use of medication to treat heart failure, as well as in the recording of past medical conditions. Finally, the investigation of data correctness suggested several issues concerning the characterization of missing data values. Many of these issues appear to be introduced while mapping the IMASIS-2 relational database contents to the ICHOM format, as the latter requires a level of detail that is not explicitly available in the coded data of an EHR.ConclusionsOverall, results of this pilot study revealed good data quality for the subset of heart failure outcomes collected at the Hospital del Mar. Nevertheless, some important data errors were identified that were caused by fundamentally different data collection practices in routine clinical care versus research, for which the ICHOM standard set was originally developed. To truly examine to what extent hospitals today are able to routinely collect the evidence of their success in achieving good health outcomes, future research would benefit from performing more extensive data quality assessments, including all data items from the ICHOM standards set and across multiple hospitals.

An integrated framework of sensing, machine learning, and augmented reality for aquaculture prawn farm management

The rapid growth of prawn farming on an international scale will play an important role in meeting the protein requirements of an expanding global population. Efficient management of the commercial ponds for healthy production of prawns is the key mantra of success in this industry. It is a necessity to maintain the water quality parameters in these ponds within specific ranges to create an ideal environment of optimal growth of healthy prawns. The current practice of water quality data collection and their usage for decision making on most farms is not efficient and does not take full advantage of the latest technologies. The research presented in this paper aimed at addressing this problem by systematic investigation and development of an integrated framework where (i) modern sensors were investigated for their suitability and deployed for continuous monitoring of the water quality variables in prawn ponds; (ii) novel machine learning models were investigated based on collected data and deployed to accurately forecast pond status over next 24 h. This provides farmers insight into upcoming situations and take necessary measures to avoid catastrophic situations; and (iii) augmented reality-based visualisation methods were investigated for improved data capture process and efficient decision making through real-time interactive interfaces. The paper presents the integrated framework as well as the details of sensing, machine learning, and augmented reality components. We found that (i) YSI EXO2 Multi-Sonde is the best sensor for continuous monitoring of prawn ponds; (ii) ForecastNet (our developed machine learning model) provides best forecasting results with symmetric mean absolute percentage error of 6.1 %, 9.6 %, and 8.5 % for dissolved oxygen, pH, and temperature; and (iii) augmented reality-based interactive interface achieves accuracy as high as 89.2 % for management decisions with at least 41 % less time. The experience of the project as presented in this paper can act as a guide for researchers as well as prawn farmers to take advantage of latest sensors, machine learning algorithms and augmented reality tools.

The face as folded object: Race and the problems with 'progress' in forensic DNA phenotyping.

Forensic DNA phenotyping (FDP) encompasses a set of technologies aimed at predicting phenotypic characteristics from genotypes. Advocates of FDP present it as the future of forensics, with an ultimate goal of producing complete, individualised facial composites based on DNA. With a focus on individuals and promised advances in technology comes the assumption that modern methods are steadily moving away from racial science. Yet in the quantification of physical differences, FDP builds upon some nineteenth- and twentieth-century scientific practices that measured and categorised human variation in terms of race. In this article I complicate the linear temporal approach to scientific progress by building on the notion of the folded object. Drawing on ethnographic fieldwork conducted in various genetic laboratories, I show how nineteenth- and early twentieth-century anthropological measuring and data-collection practices and statistical averaging techniques are folded into the ordering of measurements of skin color data taken with a spectrophotometer, the analysis of facial shape based on computational landmarks and the collection of iris photographs. Attending to the historicity of FDP facial renderings, I bring into focus how race comes about as a consequence of temporal folds.

International differences in lung cancer survival by sex, histological type and stage at diagnosis: an ICBP SURVMARK-2 Study

IntroductionLung cancer has a poor prognosis that varies internationally when assessed by the two major histological subgroups (non-small cell (NSCLC) and small cell (SCLC)).Method236 114 NSCLC and 43 167 SCLC...

Data Collection Practices for Compiling Confucian School Library Book Lists in Ming and Qing Local Gazetteers

Local gazetteers are a key source for Chinese history, but relatively little is known about how compilers obtained the information they presented in their finished works. Examining data collection practices for gazetteers is not only important to understanding the production processes and contents, but also can shed light on a variety of questions related to locality and geographical knowledge in imperial China. Tensions between standardization and localization may be revealed, the politics of geographical knowledge can be highlighted, and who was served by geographical knowledge may be shown through analysis of collection practices. This article explores data collection for Confucian school library book lists in the Ming and Qing and argues that list data came from various sources: accounting registers, on-site inspections, transcriptions of stelae and wooden plaques that recorded book acquisitions, other gazetteers, and court publications. List compilers approached their lists in different ways and lists could be comprehensive, selective, or normative in nature.

THE IPAD PRO BUILT-IN LIDAR SENSOR: 3D RAPID MAPPING TESTS AND QUALITY ASSESSMENT

Abstract. The main goal of this ongoing research is the evaluation of the iPad Pro built-in LiDAR sensor for large scale 3D rapid mapping. Different aspects have been considered from the architectural surveying perspective and several analyses were carried out focusing on the acquisition phase and the definition of best practices for data collection, the quantitative analysis on the acquired data and their 3D positional accuracy assessment, and the qualitative analysis of the achievable metric products. Despite this paper is a preliminary analysis and deeper studies in various application environment are necessary, the availability of a LiDAR sensor embedded in a tablet or mobile phone, appears promising for rapid surveying purposes. According to test outcomes, the sensor is able to rapidly acquire reliable 3D point clouds suitable for 1:200 architectural rapid mapping; the iPad Pro could represent an interesting novelty also thanks to its price (compared to standard surveying instruments), portability and limited time required both for data acquisition and processing.

The implications of the California Consumer Privacy Act (CCPA) on healthcare organizations: Lessons learned from early compliance experiences

ObjectiveIn 2018, California legislators passed the California Consumer Privacy Act (CCPA), a digital privacy regulation conferring consumers more control over their online personal information. CCPA is a significant regulation overseeing technology companies’ data collection and usage practices in the United States. This article analyzes CCPA and its implications on healthcare organizations. We elaborate on the compliance challenges that have emerged due to the interplay of the CCPA with the Health Insurance Portability and Accountability Act (HIPAA) from legal and technical/operational perspectives. MethodsQualitative methods comprising semi-structured expert interviews, qualitative data coding, and analysis were used to explore the perceptions of the practitioners on various dimensions of the policy and to obtain insights from the field. ResultsOur findings indicated that California's healthcare organizations faced several legal and technological challenges in complying with CCPA. A lack of regulatory clarity and a low likelihood of enforcement emerged as two major themes of legal concern. Poor data discovery and inventory processes, lack of sophisticated digital infrastructure, the interaction between technology and privacy professionals, and the high cost of compliance emerged as significant technological hurdles to CCPA compliance. ConclusionsDespite considerable ambiguity around the scope and jurisdiction of CCPA in the healthcare sector, healthcare organizations may be subject to CCPA, primarily when they collect personally identifiable information that is not protected health information. Such organizations may need to comply with both regulations. Furthermore, it is in their best interest to develop compliance plans proactively rather than being caught in the quandary of last-minute implementation or expensive litigation.

A Cross Sectional Survey of International Horse-Racing Authorities on Injury Data Collection and Reporting Practices For Professional Jockeys

Jockey injuries are common in professional horse-racing and can result in life-threatening or career-ending outcomes. Robust injury data are essential to understand the circumstances of injury occurrence and ultimately identify prevention opportunities. This study aimed to identify jockey injury surveillance practices of international horse-racing authorities (HRAs) and the specific data items collected and reported by each HRA. A cross-sectional survey of representatives (e.g. Chief Medical Officer) from international HRAs was conducted. An online and paper questionnaire was designed comprised of 32 questions. Questions considered the barriers and facilitators to data collection within each HRA, and where available, what data were collected and reported by HRAs. Representatives from 15 international racing jurisdictions were included, of which 12 reported collection of race day injuries or falls, using varied definitions of medical attention and time loss. Six HRAs did not have a definition for a jockey injury, and eight HRAs had no parameters for describing injury severity. Race day exposure was collected by two HRAs. Results were commonly presented by HRAs as the number of injuries (n = 9/15) or proportion of injured jockeys (n = 6/15). The lack of a designated role for collection, collation and reporting of data was the main barrier for injury surveillance. Twelve HRAs agreed that mandatory collection would be a strong facilitator to improving practice. Enhancement and standardization of international jockey injury surveillance is required to move forward with evidence informed prevention. Concurrent investigation of how reporting practices can be best supported within existing HRA structures is recommended.