scholarly journals P91 Sensitivity analyses for unmeasured confounding: recommendations for population health research

2021 ◽  
Author(s):  
Anna Pearce ◽  
Vittal Katikireddi ◽  
Alastair Leyland ◽  
Ruth Dundas
Keyword(s):  
Population Health ◽  
Health Research ◽  
Sensitivity Analyses ◽  
Unmeasured Confounding

scholarly journals Methodological Challenges When Studying Distance to Care as an Exposure in Health Research

2019 ◽  
Vol 188 (9) ◽  
pp. 1674-1681 ◽  
Author(s):  
Ellen C Caniglia ◽  
Rebecca Zash ◽  
Sonja A Swanson ◽  
Kathleen E Wirth ◽  
Modiegi Diseko ◽  
...  
Keyword(s):  
Measurement Error ◽  
Causal Inference ◽  
Selection Bias ◽  
Birth Outcomes ◽  
Health Research ◽  
Instrumental Variable ◽  
Sensitivity Analyses ◽  
Unmeasured Confounding ◽  
Instrument Selection ◽  
Distance To Care

Abstract Distance to care is a common exposure and proposed instrumental variable in health research, but it is vulnerable to violations of fundamental identifiability conditions for causal inference. We used data collected from the Botswana Birth Outcomes Surveillance study between 2014 and 2016 to outline 4 challenges and potential biases when using distance to care as an exposure and as a proposed instrument: selection bias, unmeasured confounding, lack of sufficiently well-defined interventions, and measurement error. We describe how these issues can arise, and we propose sensitivity analyses for estimating the degree of bias.

scholarly journals Assessing and piloting interoperability for population health research

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
F Estupiñán-Romero ◽  
J Gonzalez-García ◽  
E Bernal-Delgado
Keyword(s):  
Case Studies ◽  
Population Health ◽  
Health Research ◽  
Network Architecture ◽  
Digital Health ◽  
Data Extraction ◽  
Health Data ◽  
Research Network ◽  
Technical Solution ◽  
Privacy And Security

Abstract Issue/problem Interoperability is paramount when reusing health data from multiple data sources and becomes vital when the scope is cross-national. We aimed at piloting interoperability solutions building on three case studies relevant to population health research. Interoperability lies on four pillars; so: a) Legal frame (i.e., compliance with the GDPR, privacy- and security-by-design, and ethical standards); b) Organizational structure (e.g., availability and access to digital health data and governance of health information systems); c) Semantic developments (e.g., existence of metadata, availability of standards, data quality issues, coherence between data models and research purposes); and, d) Technical environment (e.g., how well documented are data processes, which are the dependencies linked to software components or alignment to standards). Results We have developed a federated research network architecture with 10 hubs each from a different country. This architecture has implied: a) the design of the data model that address the research questions; b) developing, distributing and deploying scripts for data extraction, transformation and analysis; and, c) retrieving the shared results for comparison or pooled meta-analysis. Lessons The development of a federated architecture for population health research is a technical solution that allows full compliance with interoperability pillars. The deployment of this type of solution where data remain in house under the governance and legal requirements of the data owners, and scripts for data extraction and analysis are shared across hubs, requires the implementation of capacity building measures. Key messages Population health research will benefit from the development of federated architectures that provide solutions to interoperability challenges. Case studies conducted within InfAct are providing valuable lessons to advance the design of a future pan-European research infrastructure.

scholarly journals Conducting Population Health Research during the COVID-19 Pandemic: Impacts and Recommendations

2021 ◽  
Vol 13 (6) ◽  
pp. 3320
Author(s):  
Amy R. Villarosa ◽  
Lucie M. Ramjan ◽  
Della Maneze ◽  
Ajesh George
Keyword(s):  
Data Collection ◽  
Health Services ◽  
Data Quality ◽  
Population Health ◽  
Health Research ◽  
Alternative Methods ◽  
Residential Aged Care ◽  
Recruitment Methods ◽  
Face To Face ◽  
The Impact

The COVID-19 pandemic has resulted in many changes, including restrictions on indoor gatherings and visitation to residential aged care facilities, hospitals and certain communities. Coupled with potential restrictions imposed by health services and academic institutions, these changes may significantly impact the conduct of population health research. However, the continuance of population health research is beneficial for the provision of health services and sometimes imperative. This paper discusses the impact of COVID-19 restrictions on the conduct of population health research. This discussion unveils important ethical considerations, as well as potential impacts on recruitment methods, face-to-face data collection, data quality and validity. In addition, this paper explores potential recruitment and data collection methods that could replace face-to-face methods. The discussion is accompanied by reflections on the challenges experienced by the authors in their own research at an oral health service during the COVID-19 pandemic and alternative methods that were utilised in place of face-to-face methods. This paper concludes that, although COVID-19 presents challenges to the conduct of population health research, there is a range of alternative methods to face-to-face recruitment and data collection. These alternative methods should be considered in light of project aims to ensure data quality is not compromised.

scholarly journals Stuck in the middle: a systematic review of authorship in collaborative health research in Africa, 2014–2016

2019 ◽  
Vol 4 (5) ◽  
pp. e001853 ◽  
Author(s):  
Bethany L Hedt-Gauthier ◽  
Herve Momo Jeufack ◽  
Nicholas H Neufeld ◽  
Atalay Alem ◽  
Sara Sauer ◽  
...  
Keyword(s):  
Global Health ◽  
Health Research ◽  
African Country ◽  
High Income ◽  
Sub Saharan Africa ◽  
Income Country ◽  
High Income Country ◽  
Sensitivity Analyses ◽  
Global Health Research ◽  
The Usa

BackgroundCollaborations are often a cornerstone of global health research. Power dynamics can shape if and how local researchers are included in manuscripts. This article investigates how international collaborations affect the representation of local authors, overall and in first and last author positions, in African health research.MethodsWe extracted papers on ‘health’ in sub-Saharan Africa indexed in PubMed and published between 2014 and 2016. The author’s affiliation was used to classify the individual as from the country of the paper’s focus, from another African country, from Europe, from the USA/Canada or from another locale. Authors classified as from the USA/Canada were further subclassified if the author was from a top US university. In primary analyses, individuals with multiple affiliations were presumed to be from a high-income country if they contained any affiliation from a high-income country. In sensitivity analyses, these individuals were presumed to be from an African country if they contained any affiliation an African country. Differences in paper characteristics and representation of local coauthors are compared by collaborative type using χ² tests.ResultsOf the 7100 articles identified, 68.3% included collaborators from the USA, Canada, Europe and/or another African country. 54.0% of all 43 429 authors and 52.9% of 7100 first authors were from the country of the paper’s focus. Representation dropped if any collaborators were from USA, Canada or Europe with the lowest representation for collaborators from top US universities—for these papers, 41.3% of all authors and 23.0% of first authors were from country of paper’s focus. Local representation was highest with collaborators from another African country. 13.5% of all papers had no local coauthors.DiscussionIndividuals, institutions and funders from high-income countries should challenge persistent power differentials in global health research. South-South collaborations can help African researchers expand technical expertise while maintaining presence on the resulting research.

Population Health and Social Governance: A Review, an Update, Some Clarifications, and a Response

2018 ◽  
Vol 29 (5) ◽  
pp. 731-738 ◽  
Author(s):  
Patrick O’Byrne
Keyword(s):  
Critical Theory ◽  
Population Health ◽  
Health Research ◽  
Theory And Practice ◽  
Research Approach ◽  
Qualitative Health Research ◽  
Social Governance ◽  
Depth Study ◽  
And Control

Critical theory is a paradigm that promotes viewpoints that are alternative and, at times, contrary to mainstream beliefs and dictates. In 2012, I adopted this perspective to review the role of ethnography and surmised that the data which arise from this research approach, which I described as an in-depth study of cultures, can be used to discipline and control these groups. In this edition of Qualitative Health Research, another author has critiqued this position. In this article, I review this critique, reiterate my position, update the data I used for my 2012 article, and highlight how I navigate what I feel is a tension between critical theory and practice.

scholarly journals Critical race theory as theoretical framework and analysis tool for population health research

2011 ◽  
Vol 21 (1) ◽  
pp. 81-93 ◽  
Author(s):  
Louis Graham ◽  
Shelly Brown-Jeffy ◽  
Robert Aronson ◽  
Charles Stephens
Keyword(s):  
Critical Race Theory ◽  
Population Health ◽  
Health Research ◽  
Theoretical Framework ◽  
Analysis Tool ◽  
Critical Race ◽  
Race Theory

scholarly journals The SMART Framework: Integration of Citizen Science, Community-Based Participatory Research, and Systems Science for Population Health Science in the Digital Age (Preprint)

2019 ◽  
Author(s):  
Tarun Reddy Katapally
Keyword(s):  
Big Data ◽  
Population Health ◽  
Citizen Science ◽  
Participatory Research ◽  
Health Research ◽  
Community Based Participatory Research ◽  
Health Science ◽  
Systems Science ◽  
Community Based ◽  
Science Community

UNSTRUCTURED Citizen science enables citizens to actively contribute to all aspects of the research process, from conceptualization and data collection, to knowledge translation and evaluation. Citizen science is gradually emerging as a pertinent approach in population health research. Given that citizen science has intrinsic links with community-based research, where participatory action drives the research agenda, these two approaches could be integrated to address complex population health issues. Community-based participatory research has a strong record of application across multiple disciplines and sectors to address health inequities. Citizen science can use the structure of community-based participatory research to take local approaches of problem solving to a global scale, because citizen science emerged through individual environmental activism that is not limited by geography. This synergy has significant implications for population health research if combined with systems science, which can offer theoretical and methodological strength to citizen science and community-based participatory research. Systems science applies a holistic perspective to understand the complex mechanisms underlying causal relationships within and between systems, as it goes beyond linear relationships by utilizing big data–driven advanced computational models. However, to truly integrate citizen science, community-based participatory research, and systems science, it is time to realize the power of ubiquitous digital tools, such as smartphones, for connecting us all and providing big data. Smartphones have the potential to not only create equity by providing a voice to disenfranchised citizens but smartphone-based apps also have the reach and power to source big data to inform policies. An imminent challenge in legitimizing citizen science is minimizing bias, which can be achieved by standardizing methods and enhancing data quality—a rigorous process that requires researchers to collaborate with citizen scientists utilizing the principles of community-based participatory research action. This study advances SMART, an evidence-based framework that integrates citizen science, community-based participatory research, and systems science through ubiquitous tools by addressing core challenges such as citizen engagement, data management, and internet inequity to legitimize this integration.

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