Data Collection Practices Research Articles

Green data collection strategy in the science domain for environmental sustainability

There is a recognition by modern communities world-wide, that the steadily increasing level of activities in the science domain and population growth, lead to an increase in environmental pressure on critical areas. There is a need, therefore, for stakeholders to critically appraise principles, policies, and practices that could lead to the best practices required for sustainable science activities and environmental management that is driven by green data collection, green principles, and green practices. The models involved in green data collection in science include finance-environment-community-science domain model (FECS), environment-community-science domain-finance model (ECSF), and the science domain, finance, environment-community model (SFEC). SFEC is a novel framework and is being applied in the management of active science domain, abandoned science domain, thus, providing reasonable economic and environmental benefits to the science players and non-science communities. The green data collection strategy is for enhancing social, economic, and environmental resource performance. This strategy has been tested in the Philippines. The formulation of the green data collection strategic framework involved a desktop review of previous and existing local, regional, and national data collection strategies. Consequently, visits are made to active science domain and discussions held with stakeholders. In this paper, the role of information, education, and communication have been revisited and fits adequately into the novel “green data collection model” being advanced for all players in the science domain. The absence of this framework poses the most challenging aspect of prosperity offered by the quality, quantity, diversity, and the sustainability of the science domain. Therefore, this paper has discussed the content of the green data collection strategic plan, anchored on a sustainable-controlled planning cycle. This approach could drive and sustain the harmony between man, science, and the environment.

Nonviral sexually transmitted infections in pregnancy: current controversies and new challenges.

This review provides an update of nonviral, curable sexually transmitted infections (STIs) in pregnancy and summarizes our understanding of the current issues and controversies surrounding risk factors, screening, and treatment of STIs in pregnancy primarily in high-income countries (using the United States and the United Kingdom as examples). The infections covered in this review are syphilis, gonorrhea, chlamydia, trichomoniasis, and Mycoplasma genitalium infections. Overall, limited modern data is available to update researchers and clinicians on the epidemiology and care of STIs in pregnancy. Though common risk factors can be identified among these STIs, like socioeconomic status and inadequate antenatal care, specific screening and treatment challenges vary by geography and pathogen. Wherever available, surveillance data and research evidence are often limited to nonpregnant patients, leading to imperfect pregnancy-specific risk estimates and obstetric lags in the development and adoption of new guidelines. We have identified three areas of opportunity that may enhance the effectiveness of current approaches and inform new ones: improved data collection and evidence-based screening practices; prompt and comprehensive therapy, including partner services, and evaluations of new treatment modalities; and equitable antenatal and sexual healthcare for all pregnant persons and their partners. These findings highlight the need to revisit standards of screening and management of STIs in pregnancy in high-income countries.

Research in forced displacement: guidance for a feminist and decolonial approach

The COVID-19 pandemic has deepened inequities and undermined health, human rights, and gender equality for forcibly displaced populations The ongoing pandemic has also exposed persisting power hierarchies between researchers and forcibly displaced populations These populations experience power asymmetries in their position as the so-called beneficiaries of humanitarian research and action, and are often excluded from participation in decision making about the research intended to benefit their communities Forcibly displaced women and girls are consistently categorised as vulnerable and needing protection or rescuing, which takes away their agency and power of action, while risking exploitation or abuse by the same humanitarian actors that supposedly aim to protect them We believe that applying a feminist lens is not merely about demolishing problematic structures, but also about collaboratively building up new ones for a more just world (PsycInfo Database Record (c) 2021 APA, all rights reserved)

Systematic Analysis of the Global, Regional and National Burden of Kidney Cancer from 1990 to 2017: Results from the Global Burden of Disease Study 2017

BackgroundData on kidney cancer burden are valuable for health-related policy making. ObjectiveTo report the results of the Global Burden of Disease 2017 study on global kidney cancer burden estimates grouped by gender, age, region, country or territory, and sociodemographic index (SDI) from 1990 to 2017. Design, setting, and participantsThis study is based on the Global Burden of Disease database. Outcome measurements and statistical analysisWe report here detailed estimates and temporal trends of the burden estimates of kidney cancer from 1990 to 2017, stratified by gender and age, in 195 countries and territories. We further evaluated the relationship between these estimates and the SDI, a composite indicator of income per person, years of education, and fertility as a measurement of the socioeconomic level of a country/region. The percentage change and estimated annual percentage change of incidence, mortality, and disability-adjusted life years (DALYs) were calculated to quantify temporal trends. Results and limitationsGlobally, age-standardized incidence rates, age-standardized death rates, and DALYs of kidney cancer in males exhibited an increase of 0.387%/yr, 0.345%/yr, and 0.046%/yr, respectively, from 1990 to 2017. This trend was mainly due to the increase in middle and low-middle SDI quintile countries. However, in females, decreasing trends of –0.324%/yr, –0.330%/yr, and –0.669%/yr, respectively, were observed. These trends were mainly due to the decrease in high, high-middle, and middle SDI quintile countries. Study limitations included differences in data collection practices, coding systems, and quality of data sources. ConclusionsThe burden estimate pattern of kidney cancer trends varies widely between genders and throughout the world. Low-middle and middle SDI quintile countries face the highest burden estimates, especially for males. Efforts to increase health care investment are needed in these countries. Patient summaryThe global burden estimate of kidney cancer trends increased in males; however, it decreased in females.

Exploring convolutional neural networks and spatial video for on-the-ground mapping in informal settlements

BackgroundThe health burden in developing world informal settlements often coincides with a lack of spatial data that could be used to guide intervention strategies. Spatial video (SV) has proven to be a useful tool to collect environmental and social data at a granular scale, though the effort required to turn these spatially encoded video frames into maps limits sustainability and scalability. In this paper we explore the use of convolution neural networks (CNN) to solve this problem by automatically identifying disease related environmental risks in a series of SV collected from Haiti. Our objective is to determine the potential of machine learning in health risk mapping for these environments by assessing the challenges faced in adequately training the required classification models.ResultsWe show that SV can be a suitable source for automatically identifying and extracting health risk features using machine learning. While well-defined objects such as drains, buckets, tires and animals can be efficiently classified, more amorphous masses such as trash or standing water are difficult to classify. Our results further show that variations in the number of image frames selected, the image resolution, and combinations of these can be used to improve the overall model performance.ConclusionMachine learning in combination with spatial video can be used to automatically identify environmental risks associated with common health problems in informal settlements, though there are likely to be variations in the type of data needed for training based on location. Success based on the risk type being identified are also likely to vary geographically. However, we are confident in identifying a series of best practices for data collection, model training and performance in these settings. We also discuss the next step of testing these findings in other environments, and how adding in the simultaneously collected geographic data could be used to create an automatic health risk mapping tool.

Constructing a queer population? Asking about sexual orientation in Scotland’s 2022 census

ABSTRACT For the first time, Scotland’s 2022 census will ask a question about sexual orientation. Correspondence between National Records of Scotland, the Scottish Parliament’s Culture, Tourism, Europe and External Affairs Committee and campaign groups present insights into decisions made, the uneasy relationship between queer identities and state data collection practices, and the question of who is counted when we count LGBTQ people. Building on Foucault’s critique of projects that construct population knowledge, the census is framed primarily as a tool to facilitate the state’s capacity to govern. My engagement in the design process enabled me to critically examine decisions made about the exclusion of non-binary identities and the use of predictive text technology. These decisions demonstrate how the design process constructed a queer population that ‘made sense’ to the heteronormative majority and ‘designed-out’ queer lives that the state did not wish to bring into being.

Responsible innovation for digital identity systems

Abstract Digital identity (eID) systems are a crucial piece in the digital services ecosystem. They connect individuals to a variety of socioeconomic opportunities but can also reinforce power asymmetries between organizations and individuals. Data collection practices can negatively impact an individual’s right to privacy, autonomy, and self-determination. Protecting individual rights, however, may be at odds with imperatives of profit maximization or national security. The use of eID technologies is hence highly contested. Current approaches to governing eID systems have been unable to fully address the trade-offs between the opportunities and risks associated with these systems. The responsible innovation (RI) literature provides a set of principles to govern disruptive innovations, such as eID systems, toward societally desirable outcomes. This article uses RI principles to develop a framework to govern eID systems in a more inclusive, responsible, and user-centered manner. The proposed framework seeks to complement existing practices for eID system governance by bringing forth principles of deliberation and democratic engagement to build trust amongst stakeholders of the eID system and deliver shared socioeconomic benefits.

Best practices of neurophysiological data collection for media message evaluation in social campaigns

Cognitive neuroscience techniques have become a great complement to traditional methods in marketing research. However, many difficulties have arisen, such as the collection of reliable data, processing and proper analysis. The paper presents good practices of collecting neurophysiological data for the evaluation of media messages in social campaigns. For this purpose, the most common difficulties during signal recording for devices such as EEG, GSR, HR, Eye Tracker were identified. The problems that arose were assigned to three main groups that could be affected, i.e.the examing person, the examing enviroment and the examing equipment. In the final stage, solutions were proposed to reduce or eliminate them.

Das Recht der Nachrichtendienste: Missstände, Entwicklungen und Perspektiven eines Rechtsgebiets in der Findungsphase

The law governing the German intelligence services lacks a consistent concept, is non-transparent, fragmented and in urgent need of reform. In May 2020, the First Senate of the Federal Constitutional Court held that the Federal Intelligence Service (Bundesnachrichtendienst - BND) is bound by the fundamental rights of the Basic Law when conducting telecommunications surveillance of foreigners in other countries (so-called Foreign-Foreign Strategic Surveillance), and that the statutory bases in their current design violate the fundamental right to the privacy of telecommunication and freedom of the press. The judgment put an end to the long-running discussion about whether intelligence operations abroad are suitable for statutory regulation at all. Moreover, the Constitutional Court’s decision provided the impetus for one of the most significant reforms in recent German security law. By April 2021, the amendment of the BND Act was finally on the books. It will enter into force in January 2022. It codifies important new rules about the practice, authorization and oversight of foreign data collection by the BND as well as legal requirements for Germany’s participation in international intelligence cooperation. The reform’s provisions implement the constitutional requirements, as stated in the judgement, almost literally. Nonethele⁠ss, the reform created a number of new problems and left major deficits in German intelligence law unresolved. It is far from creating a clear and consistent legal framework for the activities of the three federal intelligence services, in particular their surveillance practices. The article outlines the major shortcomings, developments and perspectives in this field of security law.

Rejecting Test Surveillance in Higher Education

The rise of remote proctoring software during the COVID-19 pandemic illustrates the dangers of surveillance-enabled pedagogy built on the belief that students can’t be trusted. These services, which deploy a range of identification protocols, computer and internet access limitations, and human or automated observation of students as they take tests remotely, are marketed as necessary to prevent cheating. But the success of these services in their stated goal is ill- supported at best and discredited at worst, particularly given their highly over- inclusive criteria for “suspicious” behavior. Meanwhile, the harms they inflict on students are clear: severe anxiety among test-takers, concerning data collection and use practices, and discriminatory flagging of students of color and students with disabilities have provoked widespread outcry from students, professors, privacy advocates, policymakers, and sometimes universities themselves. To make matters worse, the privacy and civil rights laws most relevant to the use of these services are generally inadequate to protect students from the harms they inflict.Colleges and universities routinely face difficult decisions that require reconciling conflicting interests, but whether to use remote proctoring software isn’t one of them. Remote proctoring software is not pedagogically beneficial, institutionally necessary, or remotely unavoidable, and its use further entrenches inequities in higher education that schools should be devoted to rooting out. Colleges and universities should abandon remote proctoring software, and apply the lessons from this failed experiment to their other existing or potential future uses of surveillance technologies and automated decision-making systems that threaten students’ privacy, access to important life opportunities, and intellectual freedom.

(mis)Informed Consent in Australia

(mis)Informed Consent in Australia

Brain injuries: health care capacity and policy in Georgia.

:Background:Over 90% of morbidity and mortality associated with traumatic brain injury (TBI) occurs in low- and middle-income countries. Lack of reliable, high-quality data regarding TBI prevention and care hinders the ability to reduce TBI burden. We sought to identify current TBI data collection practices and capacity in Georgia, focusing on pre-hospital, hospital, and rehabilitation treatment.Methods:The eight level I and two level II Trauma Hospitals in Georgia with the highest number of TBI admissions in 2017 were selected for study. A semi-structured survey about various aspects of TBI care was designed and semi-structured interviews of healthcare providers treating TBI patients (e.g. neurologists, neurosurgeons) were conducted based on this survey. Results:Pre-hospital triage protocols were not routinely used to match patient treatment needs with hospital capacity. All hospitals provided specialist care for TBI 24 hours/day. MRI was available at only three (30%) centers, and in-hospital rehabilitation units were available in only one (10%). No center used a defined protocol for treating TBI patients and no national protocol exists.Conclusions:Even among the largest, most highly specialized hospitals in Georgia, TBI care varies in terms of diagnostic and treatment protocols. While TBI specialists are available, diagnostic equipment often is not. Gaps in pre-hospital coordination and access to rehabilitation services exist and provide areas of focus for future investment in reducing TBI burden.

Volume 49 Paper 3 pp. 57 – 85 July 2021 Evidence Quality, Transparency, and Translucency for Replication in Information Systems Survey Research

Replicability represents the cornerstone of reliable development in science. In this paper, we develop a framework for enhancing current data-collection practices’ replicability in survey research in information systems. To develop the framework, we built on literature, benchmarks of various scientific associations, and a review of policies and best practices in leading business journals. The framework identifies best practices for transparently collecting data, sharing data and methods, and developing high-quality evidence. We analyzed 82 recently published survey research in nine IS journals as a sample that represents high-quality IS research to identify their replicability and found that not one papers provided enough details for replication. We conclude by discussing our framework’s implications for researchers, journals, and scientific institutions and the role that these entities can play in enhancing IS research’s replicability.

Joint allies: Benefits and tensions of co-producing a prostate cancer app for, and with, the Black British African-Caribbean community

ABSTRACT In this paper we use a case study, the co-production of a prostate cancer app with, and for, Black British African-Caribbean communities, to discuss benefits and tensions of inclusive practice and allyship. We view our collaborators as joint partners, and joint allies, for the Black British African-Caribbean community. Here, we document the research process and highlight successful aspects of our collaboration such as mentoring, recruitment, ideas on the format and presentation of the app, supportive data collection practices, useful community feedback and promotion of the app. We also highlight points in the research process that in hindsight needed more discussion and careful negotiation. We end with some recommendations based on our experience.

Comprehensive or Comprehensible Experience? A Case Study of Religion and Traumatic Bereavement

The first half of this article provides a brief overview of two respective projects concerning traumatic bereavement, in which religious faith appeared to feature amid a constellation of significant coping and sense-making mechanisms for survivors. After presenting some illustrative examples of the kind of data produced in the course of our research, the second half of the article develops a retrospectively critical appraisal of our data collection and corresponding analysis practices. In questioning the extent to which our accounts of our participants’ accounts can be considered adequate representations of social order, we critically explore the relative potential of ‘reflexivity’ for bridging the experiential gap between researchers and participants. Taken together, these reflections prompt a return to the salutary question: what counts as sociologically ‘see-able’?

Editor’s Note

Editor’s Note

Developing a national birth cohort for child health research using a hospital admissions database in England: The impact of changes to data collection practices.

National birth cohorts derived from administrative health databases constitute unique resources for child health research due to whole country coverage, ongoing follow-up and linkage to other data sources. In England, a national birth cohort can be developed using Hospital Episode Statistics (HES), an administrative database covering details of all publicly funded hospital activity, including 97% of births, with longitudinal follow-up via linkage to hospital and mortality records. We present methods for developing a national birth cohort using HES and assess the impact of changes to data collection over time on coverage and completeness of linked follow-up records for children. We developed a national cohort of singleton live births in 1998-2015, with information on key risk factors at birth (birth weight, gestational age, maternal age, ethnicity, area-level deprivation). We identified three changes to data collection, which could affect linkage of births to follow-up records: (1) the introduction of the "NHS Numbers for Babies (NN4B)", an on-line system which enabled maternity staff to request a unique healthcare patient identifier (NHS number) immediately at birth rather than at civil registration, in Q4 2002; (2) the introduction of additional data quality checks at civil registration in Q3 2009; and (3) correcting a postcode extraction error for births by the data provider in Q2 2013. We evaluated the impact of these changes on trends in two outcomes in infancy: hospital readmissions after birth (using interrupted time series analyses) and mortality rates (compared to published national statistics). The cohort covered 10,653,998 babies, accounting for 96% of singleton live births in England in 1998-2015. Overall, 2,077,929 infants (19.5%) had at least one hospital readmission after birth. Readmission rates declined by 0.2% percentage points per annual quarter in Q1 1998 to Q3 2002, shifted up by 6.1% percentage points (compared to the expected value based on the trend before Q4 2002) to 17.7% in Q4 2002 when NN4B was introduced, and increased by 0.1% percentage points per annual quarter thereafter. Infant mortality rates were under-reported by 16% for births in 1998-2002 and similar to published national mortality statistics for births in 2003-2015. The trends in infant readmission were not affected by changes to data collection practices in Q3 2009 and Q2 2013, but the proportion of unlinked mortality records in HES and in ONS further declined after 2009. HES can be used to develop a national birth cohort for child health research with follow-up via linkage to hospital and mortality records for children born from 2003 onwards. Re-linking births before 2003 to their follow-up records would maximise potential benefits of this rich resource, enabling studies of outcomes in adolescents with over 20 years of follow-up.

Using the Canadian Institute for Health Information’s Information Quality Framework to Support Integration and Utilization of Complex, Multi-Jurisdictional Data

The Canadian Institute for Health Information (CIHI) provides essential information on Canada’s health systems and the health of Canadians. This presentation discusses information quality’s role in the integration and utilization of CIHI’s complex, multi-sector and multi-jurisdictional data.
 IntroductionCIHI’s Data and Information Quality Program is recognized internationally for its comprehensiveness and high standards. As the need for linked data research increases, the requirements on quality continue to grow. CIHI’s multi-sector, multi-jurisdictional healthcare system and the varying health policies, care delivery models, and data collection practices that go with it pose challenges for researchers as they try to pull the data together in a comprehensive way. CIHI’s Information Quality Framework forms the foundation for addressing these challenges and ensuring data are fit for integration and are properly utilized.
 Objectives and ApproachIn 2019, a connected data quality project was initiated to improve the usability of CIHI’s analytical data. Information quality framework concepts were applied across CIHI data sources to better understand data linkage challenges, measure inconsistencies across data sources, identify opportunities to improve data and standards, and develop resources to support users.
 ResultsFindings from the project identified key connected data quality activities for the organization to operationalize. These focus on quality assessment and reporting; harmonization of data standards; expanded documentation and analytical resources; data classification and profiling tools to support descriptive analysis; and new source of truth and pre-linked datasets. Quality activities were prioritized based on need and complexity, and “connected data teams” were established to carry out the work.
 Conclusion / ImplicationsExpansion of CIHI’s quality framework across data sources facilitates its data linkage capabilities and “connected data” use. It enables the evolution of CIHI’s analytical environments and information products from being database specific to integrated-data driven, and facilitates the use of CIHI’s analytical data for research.

Iefieldkit: Commands for primary data collection and cleaning

Data collection and cleaning workflows implement highly repetitive but extremely important processes. In this article, we introduce iefieldkit, a package developed to standardize and simplify best practices for high-quality primary data collection across the World Bank’s Development Research Group Impact Evaluations department. iefieldkit automates error-checking for electronic Open Data Kit-based survey modules such as those implemented in SurveyCTO; duplicate checking and resolution; data cleaning, including renaming, labeling, recoding, and survey harmonization; and codebook creation.

179 Open discussion of data bottlenecks in the dairy industry: The Dairy Brain Coordinated Innovation Network

Abstract New dairy farm management technologies produce vast amounts of data. Although more data support better decisions, managing data also comes with critical challenges. In an effort to create awareness and develop guidelines for data management in the dairy industry, the University of Wisconsin Dairy Brain project is nurturing a Coordinated Innovation Network (CIN). The USDA definition of a CIN is a large “community that addresses bottlenecks [...] by bringing together experts from different disciplines and domains to identify innovative and synergistic solutions.” The Dairy Brain CIN currently has 81 members from 9 different countries. It is a growing community open to anyone who is interested in being part of the process of data collection, data engineering techniques and data usage in dairy farms. One of the objectives of the CIN is to write some design documents regarding data issues. During the first official meeting in September 2019, several CIN subcommittees were created with the purpose to write and publish opinion articles about some critical topics: 1) data security and ownership; 2) best practices of data collection and communication; 3) farm adoption; and 4) creating value from data. The idea behind these opinion articles was to generate industry-wide awareness and to start a meaningful discussion. These opinion articles have been published in Hoard’s Dairyman magazine as a series in the following dates: February 10, March 25, April 10, April 25 and May 10, 2020. In addition, an online forum was created to encourage larger industry participation. These opinion articles are the foundation of more in-depth technical articles. This presentation will focus on summarizing the content of the published opinion articles and their subsequent deliberations. The presentation will promote further discussion and invite stakeholders to join the Dairy Brain CIN and/or participate and contribute in the wider discussion.