scholarly journals Reproducible Research: A Retrospective

2021 ◽  
Vol 42 (1) ◽  
Author(s):  
Roger D. Peng ◽  
Stephanie C. Hicks
Keyword(s):  
Public Health ◽  
Health Research ◽  
Scientific Discovery ◽  
Scientific Progress ◽  
Original Data ◽  
Public Health Research ◽  
Current Status ◽  
Reproducible Research ◽  
Annual Review ◽  
Publication Date

Advances in computing technology have spurred two extraordinary phenomena in science: large-scale and high-throughput data collection coupled with the creation and implementation of complex statistical algorithms for data analysis. These two phenomena have brought about tremendous advances in scientific discovery but have raised two serious concerns. The complexity of modern data analyses raises questions about the reproducibility of the analyses, meaning the ability of independent analysts to recreate the results claimed by the original authors using the original data and analysis techniques. Reproducibility is typically thwarted by a lack of availability of the original data and computer code. A more general concern is the replicability of scientific findings, which concerns the frequency with which scientific claims are confirmed by completely independent investigations. Although reproducibility and replicability are related, they focus on different aspects of scientific progress. In this review, we discuss the origins of reproducible research, characterize the current status of reproducibility in public health research, and connect reproducibility to current concerns about replicability of scientific findings. Finally, we describe a path forward for improving both the reproducibility and replicability of public health research in the future. Expected final online publication date for the Annual Review of Public Health, Volume 42 is April 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals An Empirical Study of Applying Statistical Disclosure Control Methods to Public Health Research

2019 ◽  
Vol 16 (22) ◽  
pp. 4519
Author(s):  
Amanda M. Y. Chu ◽  
Benson S. Y. Lam ◽  
Agnes Tiwari ◽  
Mike K. P. So
Keyword(s):  
Public Health ◽  
Health Care ◽  
Empirical Study ◽  
Health Research ◽  
Original Data ◽  
Public Health Research ◽  
Statistical Disclosure Control ◽  
Data Perturbation ◽  
Disclosure Control ◽  
Statistical Disclosure

Patient data or information collected from public health and health care surveys are of great research value. Usually, the data contain sensitive personal information. Doctors, nurses, or researchers in the public health and health care sector do not analyze the available datasets or survey data on their own, and may outsource the tasks to third parties. Even though all identifiers such as names and ID card numbers are removed, there may still be some occasions in which an individual can be re-identified via the demographic or particular information provided in the datasets. Such data privacy issues can become an obstacle in health-related research. Statistical disclosure control (SDC) is a useful technique used to resolve this problem by masking and designing released data based on the original data. Whilst ensuring the released data can satisfy the needs of researchers for data analysis, there is high protection of the original data from disclosure. In this research, we discuss the statistical properties of two SDC methods: the General Additive Data Perturbation (GADP) method and the Gaussian Copula General Additive Data Perturbation (CGADP) method. An empirical study is provided to demonstrate how we can apply these two SDC methods in public health research.

Risks and Opportunities to Ensure Equity in the Application of Big Data Research in Public Health

2021 ◽  
Vol 43 (1) ◽  
Author(s):  
Paul Wesson ◽  
Yulin Hswen ◽  
Gilmer Valdez ◽  
Kristefer Stojanovski ◽  
Margaret A. Handley
Keyword(s):  
Public Health ◽  
Big Data ◽  
Data Augmentation ◽  
Public Health Research ◽  
Machine Learning Algorithms ◽  
Annual Review ◽  
Publication Date ◽  
Medical Claims ◽  
Marginalized Communities ◽  
Big Data Applications

The big data revolution presents an exciting frontier to expand public health research, broadening the scope of research and increasing the precision of answers. Despite these advances, scientists must be vigilant against also advancing potential harms toward marginalized communities. In this review, we provide examples in which big data applications have (unintentionally) perpetuated discriminatory practices, while also highlighting opportunities for big data applications to advance equity in public health. Here, big data is framed in the context of the five Vs (volume, velocity, veracity, variety, and value), and we propose a sixth V, virtuosity, which incorporates equity and justice frameworks. Analytic approaches to improving equity are presented using social computational big data, fairness in machine learning algorithms, medical claims data, and data augmentation as illustrations. Throughout, we emphasize the biasing influence of data absenteeism and positionality and conclude with recommendations for incorporating an equity lens into big data research. Expected final online publication date for the Annual Review of Public Health, Volume 43 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Qualitative Research Methods in Chronic Disease: Introduction and Opportunities to Promote Health Equity

2021 ◽  
Vol 43 (1) ◽  
Author(s):  
Rachel C. Shelton ◽  
Morgan M. Philbin ◽  
Shoba Ramanadhan
Keyword(s):  
Public Health ◽  
Qualitative Research ◽  
Chronic Disease ◽  
Qualitative Methods ◽  
Health Equity ◽  
Public Health Research ◽  
Annual Review ◽  
Publication Date ◽  
Research Questions ◽  
Evidence Generation

Public health research that addresses chronic disease has historically underutilized and undervalued qualitative methods. This has limited the field's ability to advance ( a) a more in-depth understanding of the factors and processes that shape health behaviors, ( b) contextualized explanations of interventions’ impacts (e.g., why and how something did or did not work for recipients and systems), and ( c) opportunities for building and testing theories. We introduce frameworks and methodological approaches common to qualitative research, discuss how and when to apply them in order to advance health equity, and highlight relevant strengths and challenges. We provide an overview of data collection, sampling, and analysis for qualitative research, and we describe research questions that can be addressed by applying qualitative methods across the continuum of chronic disease research. Finally, we offer recommendations to promote the strategic application of rigorous qualitative methods, with an emphasis on priority areas to enhance health equity across the evidence generation continuum. Expected final online publication date for the Annual Review of Public Health, Volume 43 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Utilizing asynchronous email interviews for health research: overview of benefits and drawbacks

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Michelle Amri ◽  
Christina Angelakis ◽  
Dilani Logan
Keyword(s):  
Public Health ◽  
Data Collection ◽  
Data Quality ◽  
Health Research ◽  
Geographic Location ◽  
Public Health Research ◽  
Data Accuracy ◽  
Global Public Health ◽  
Snowball Sampling ◽  
Face To Face

Abstract Objective Through collating observations from various studies and complementing these findings with one author’s study, a detailed overview of the benefits and drawbacks of asynchronous email interviewing is provided. Through this overview, it is evident there is great potential for asynchronous email interviews in the broad field of health, particularly for studies drawing on expertise from participants in academia or professional settings, those across varied geographical settings (i.e. potential for global public health research), and/or in circumstances when face-to-face interactions are not possible (e.g. COVID-19). Results Benefits of asynchronous email interviewing and additional considerations for researchers are discussed around: (i) access transcending geographic location and during restricted face-to-face communications; (ii) feasibility and cost; (iii) sampling and inclusion of diverse participants; (iv) facilitating snowball sampling and increased transparency; (v) data collection with working professionals; (vi) anonymity; (vii) verification of participants; (viii) data quality and enhanced data accuracy; and (ix) overcoming language barriers. Similarly, potential drawbacks of asynchronous email interviews are also discussed with suggested remedies, which centre around: (i) time; (ii) participant verification and confidentiality; (iii) technology and sampling concerns; (iv) data quality and availability; and (v) need for enhanced clarity and precision.

scholarly journals Reporting the methods used in public health research and practice

2017 ◽  
Vol 1 ◽  
pp. 89-89 ◽  
Author(s):  
Donna F. Stroup ◽  
C. Kay Smith ◽  
Benedict I. Truman
Keyword(s):  
Public Health ◽  
Health Research ◽  
Public Health Research ◽  
Research And Practice
Sign in / Sign up

Export Citation Format

Share Document